--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\ibabenko\ASU Dropbox\Ilona Babenka\_NONPROFIT CEO PAY\RFS_code\RFS_CodeFinal\Logfile_rfs_may2025.log
  log type:  text
 opened on:  22 May 2025, 13:20:53

. do "C:\Users\ibabenko\AppData\Local\Temp\STD61c8_000000.tmp"

. *Change path here to the folder with code files
. cd "C:\Users\ibabenko\ASU Dropbox\Ilona Babenka\_NONPROFIT CEO PAY\RFS_code\RFS_CodeFinal"
C:\Users\ibabenko\ASU Dropbox\Ilona Babenka\_NONPROFIT CEO PAY\RFS_code\RFS_CodeFinal

. *cd "D:\db\Dropbox\IlonaBen\RFS_code\\RFS_CodeFinal"
. 
. *install stata packages if not installed already
. ssc install estout, replace
checking estout consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install asdoc, replace
checking asdoc consistency and verifying not already installed...
all files already exist and are up to date.

. 
. *Fig 1. Nonprofit Industries (plotted in Excel)
. use ceo_apr22, clear

. tab ntee1

      ntee1 |      Freq.     Percent        Cum.
------------+-----------------------------------
          A |      4,158        4.82        4.82
          B |     17,218       19.97       24.80
          C |      1,049        1.22       26.02
          D |        732        0.85       26.86
          E |     22,597       26.21       53.08
          F |      1,614        1.87       54.95
          G |        881        1.02       55.97
          H |        837        0.97       56.94
          I |        487        0.56       57.51
          J |      4,354        5.05       62.56
          K |        847        0.98       63.54
          L |      1,317        1.53       65.07
          M |        114        0.13       65.20
          N |      6,236        7.23       72.44
          O |        555        0.64       73.08
          P |      8,589        9.96       83.05
          Q |      1,283        1.49       84.53
          R |        185        0.21       84.75
          S |      5,003        5.80       90.55
          T |      2,837        3.29       93.84
          U |        947        1.10       94.94
          V |        216        0.25       95.19
          W |      1,371        1.59       96.78
          X |        451        0.52       97.31
          Y |      2,320        2.69      100.00
          Z |          2        0.00      100.00
------------+-----------------------------------
      Total |     86,200      100.00

. 
. /*
> A) Art, Culture, and Humanities
> B) Education Institutions and Related Activities
> C) Environmental Quality Protection and Beautification
> D) Animal Related
> E) Health General and Rehabilitative
> F) Mental Health Crisis Intervention
> G) Disease Disorders Medical Disciplines
> H) Medical Research
> I) Crime Legal Related
> J) Employment Job Related
> K) Food Agriculture and Nutrition
> L) Housing Shelter
> M) Public Safety Disaster Preparedness and Relief
> N) Recreation Sports Leisure Athletics
> O) Youth Development
> P) Human Services Multipurpose and other
> Q) International Foreign Affairs and National Security
> R) Civil Rights Social Action Advocacy
> S) Community Improvement Capacity Building
> T) Philanthropy Voluntarism and Grant making Foundations
> U) Science and Technology Research Institutes Services
> V) Social Science Research Institutes
> W) Public Society Benefit Multipurpose
> X) Religion Related Spiritual Development
> Y) Mutual, Membership Benefit Organizations, Other
> Z) Internal Use
> */
. 
. *Fig 2. CEO Compensation vs. Firm Size
. use fig2_apr22, clear

. twoway (scatter avg_log_ceo_rev_comm avg_log_rev_comm, msymbol(O)) (scatter avg_log_ceo_rev_char avg_log_rev_char, msymbol(T)) (scatter avg_log_ceo_rev_profit avg_log_rev_profit, msymbol(S)), ytitle
> (Log(Total Compensation)) xlabel(#5) xtitle(Log(Revenue)) bgcolor(white) graphregion(color(none))

. graph export "Output\Fig2.png", as(png) name("Graph") replace
file Output\Fig2.png saved as PNG format

. 
. *Fig 3. CEO time series (plotted in Excel)
. use ceo_apr22, clear

. reghdfe log_tdc1_z ib2014.fyear2##ny, abs(fyear2 ein) cluster(state)
(dropped 1779 singleton observations)
note: 2008bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2009bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2010bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2011bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2012bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2013bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2015bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2016bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2017bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2018bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 7 iterations)
note: 2008.fyear2 omitted because of collinearity
note: 2009.fyear2 omitted because of collinearity
note: 2010.fyear2 omitted because of collinearity
note: 2011.fyear2 omitted because of collinearity
note: 2012.fyear2 omitted because of collinearity
note: 2013.fyear2 omitted because of collinearity
note: 2015.fyear2 omitted because of collinearity
note: 2016.fyear2 omitted because of collinearity
note: 2017.fyear2 omitted because of collinearity
note: 2018.fyear2 omitted because of collinearity

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(  11,     52) =       3.94
Statistics robust to heteroskedasticity           Prob > F        =     0.0004
                                                  R-squared       =     0.9278
                                                  Adj R-squared   =     0.9155
                                                  Within R-sq.    =     0.0002
Number of clusters (state)   =         53         Root MSE        =     0.2182

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_z | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      fyear2 |
       2008  |          0  (omitted)
       2009  |          0  (omitted)
       2010  |          0  (omitted)
       2011  |          0  (omitted)
       2012  |          0  (omitted)
       2013  |          0  (omitted)
       2015  |          0  (omitted)
       2016  |          0  (omitted)
       2017  |          0  (omitted)
       2018  |          0  (omitted)
             |
        1.ny |   .0961747   .0362669     2.65   0.011     .0233999    .1689496
             |
   fyear2#ny |
     2008 1  |  -.0087314   .0083581    -1.04   0.301    -.0255031    .0080404
     2009 1  |  -.0047452   .0075579    -0.63   0.533    -.0199113    .0104209
     2010 1  |  -.0033643   .0055643    -0.60   0.548      -.01453    .0078014
     2011 1  |   .0016146   .0048983     0.33   0.743    -.0082145    .0114438
     2012 1  |   .0064456   .0046736     1.38   0.174    -.0029328    .0158239
     2013 1  |  -.0006575   .0030261    -0.22   0.829    -.0067299    .0054149
     2015 1  |  -.0113648   .0037244    -3.05   0.004    -.0188384   -.0038911
     2016 1  |  -.0090479   .0049371    -1.83   0.073    -.0189548    .0008591
     2017 1  |  -.0167382   .0056759    -2.95   0.005    -.0281278   -.0053486
     2018 1  |  -.0196887   .0072593    -2.71   0.009    -.0342556   -.0051218
             |
       _cons |   6.038945   .0041271  1463.23   0.000     6.030664    6.047227
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
      fyear2 |        11           0          11     |
         ein |     12332           1       12331     |
-----------------------------------------------------+

. 
. *Fig 4. NonCEO time series  (plotted in Excel)
. use nonceo_apr22, clear

. reghdfe log_tdc1_w ib2014.fyear2##ny, abs(fyear2 ein) cluster(state)
(dropped 563 singleton observations)
note: 2008bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2009bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2010bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2011bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2012bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2013bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2015bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2016bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2017bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: 2018bn.fyear2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 8 iterations)
note: 2008.fyear2 omitted because of collinearity
note: 2009.fyear2 omitted because of collinearity
note: 2010.fyear2 omitted because of collinearity
note: 2011.fyear2 omitted because of collinearity
note: 2012.fyear2 omitted because of collinearity
note: 2013.fyear2 omitted because of collinearity
note: 2015.fyear2 omitted because of collinearity
note: 2016.fyear2 omitted because of collinearity
note: 2017.fyear2 omitted because of collinearity
note: 2018.fyear2 omitted because of collinearity

HDFE Linear regression                            Number of obs   =    396,883
Absorbing 2 HDFE groups                           F(  11,     52) =       6.76
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7165
                                                  Adj R-squared   =     0.7094
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.3058

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      fyear2 |
       2008  |          0  (omitted)
       2009  |          0  (omitted)
       2010  |          0  (omitted)
       2011  |          0  (omitted)
       2012  |          0  (omitted)
       2013  |          0  (omitted)
       2015  |          0  (omitted)
       2016  |          0  (omitted)
       2017  |          0  (omitted)
       2018  |          0  (omitted)
             |
        1.ny |   .0442614   .0237135     1.87   0.068    -.0033232     .091846
             |
   fyear2#ny |
     2008 1  |  -.0075872   .0096267    -0.79   0.434    -.0269045    .0117301
     2009 1  |  -.0278582   .0082696    -3.37   0.001    -.0444525    -.011264
     2010 1  |   .0040134   .0051465     0.78   0.439    -.0063138    .0143407
     2011 1  |  -.0059083   .0037939    -1.56   0.125    -.0135212    .0017046
     2012 1  |  -.0037437   .0026258    -1.43   0.160    -.0090128    .0015253
     2013 1  |   -.003354   .0028204    -1.19   0.240    -.0090134    .0023055
     2015 1  |   .0011425   .0024766     0.46   0.646    -.0038272    .0061122
     2016 1  |  -.0007443   .0029298    -0.25   0.800    -.0066233    .0051347
     2017 1  |  -.0006575   .0037979    -0.17   0.863    -.0082785    .0069635
     2018 1  |  -.0004757   .0050603    -0.09   0.925    -.0106301    .0096786
             |
       _cons |   5.707257   .0031334  1821.43   0.000     5.700969    5.713544
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
      fyear2 |        11           0          11     |
         ein |      9736           1        9735     |
-----------------------------------------------------+

. 
. *T1.A. Summary stats 
. use both_apr22, clear

. 
. asdoc tabstat j_total_comp_w j_base_comp_w j_bonus_incntv_comp_w j_oth_rptble_comp_w j_def_comp_w j_nontxbl_comp_w ceo hrs_t1 if sample==1, stats(mean sd p10 p50 p90 N) dec(2) label save(Output\T1A.
> doc) replace

             |      Mean         SD        p10        p50        p90          N 
-------------+-----------------------------------------------------------------
j_total_co~w |  405.4635   362.3452     168.24    275.277    787.564     450771 
j_base_com~w |  277.8456   188.8639     134.21    212.125    507.389     450771 
j_bonus_in~w |  46.21092   110.2449          0         .8    125.147     450771 
j_oth_rptb~w |  24.23794   71.56573          0      1.188     53.386     450771 
j_def_comp_w |  30.06223   53.25843          0     14.883      64.42     450771 
j_nontxbl_~w |  17.79187   13.63293      2.081     16.131     32.498     450771 
         ceo |  .1198325   .3247659          0          0          1     450771 
      hrs_t1 |  43.22024   6.598513         40         40         54     450771 
(file Output\T1A.doc not found)
Click to Open File:  Output\T1A.doc

. 
. *T1.B. Summary stats 
. use ceo_apr22, clear

. 
. *number of unique organizations in the main dataset
. distinct ein 

----------------------------
     |     total   distinct
-----+----------------------
 ein |     86200      14111
----------------------------

. 
. asdoc tabstat j_total_comp_w j_base_comp_w j_bonus_incntv_comp_w j_oth_rptble_comp_w j_def_comp_w j_nontxbl_comp_w hrs_t1 if sample==1, stats(mean sd p10 p50 p90 N) dec(2) label save(Output\T1B.doc)
>  replace

             |      Mean         SD        p10        p50        p90          N 
-------------+-----------------------------------------------------------------
j_total_co~w |  601.2397   695.0603    186.883    356.011   1269.425      84421 
j_base_com~w |  367.7496   268.5155        155    276.829    709.856      84421 
j_bonus_in~w |  83.74115   215.9785          0          0    233.173      84421 
j_oth_rptb~w |  61.29465   214.5084          0       .578    114.618      84421 
j_def_comp_w |   47.6761   107.5303          0       15.6    110.127      84421 
j_nontxbl_~w |  20.10072   19.97658          0     16.176     40.439      84421 
      hrs_t1 |  43.48242   7.082053         40         40         55      84421 
(file Output\T1B.doc not found)
Click to Open File:  Output\T1B.doc

. 
. *T1.C
. use ceo_apr22, clear

. asdoc tabstat tot_nonceo assets_scale rev_scale debtat_w bd_ind_w coi whistle audit_cmte family comp_cmte_fill consultant_fill employ_cntrct_fill oth_firms990_fill  compceo_process charity50 femalec
> eo contri_scale_w employees_scale_w volunteer_scale_w rev_emp_w program_w wage_emp_w if sample==1, stats(mean sd p10 p50 p90 N) dec(2) label save(Output\T1C.doc) replace

             |      Mean         SD        p10        p50        p90          N 
-------------+-----------------------------------------------------------------
  tot_nonceo |  5.498786   5.041831          0          4         15      84421 
assets_scale |  273.5967   1559.381   10.96901    61.4968   454.4246      84421 
   rev_scale |  130.4816   602.6464   5.191396   28.60195   257.0107      84421 
    debtat_w |  .3770827   .3286728   .0350303   .3071386   .8011758      84418 
    bd_ind_w |  .8772162   .2314965   .6363636   .9795918          1      84382 
         coi |  .9394227   .2385548          1          1          1      84421 
     whistle |  .8721882   .3338821          0          1          1      84421 
  audit_cmte |  .9313441   .2528696          1          1          1      84421 
      family |  .2159178     .41146          0          0          1      84421 
comp_cmte_~l |  .5572429   .4967154          0          1          1      84421 
consultant~l |   .285853   .4518224          0          0          1      84421 
employ_cnt~l |  .3275133    .469309          0          0          1      84421 
oth_firms9~l |   .657597   .4745164          0          1          1      84421 
compceo_pr~s |  .8965068   .3046038          0          1          1      84421 
   charity50 |  .2685026   .4431836          0          0          1      71098 
   femaleceo |  .2377247   .4256941          0          0          1      47555 
contri_sca~w |  14.16486   41.22011          0       1.75   29.97766      84421 
employees_~w |  8.838935   17.01927         .2       2.71      22.98      84421 
volunteer_~w |  5.979963   21.82891          0         .5        9.5      84421 
   rev_emp_w |  .3272177   .7713719   .0397797   .1078554   .6226631      84421 
   program_w |   .829292   .1056751   .7098215   .8470041   .9366158      65938 
  wage_emp_w |  61.50234   47.30591   18.74527   49.74843   116.2152      84421 
(file Output\T1C.doc not found)
Click to Open File:  Output\T1C.doc

. 
. *T1.D
. use t2_panel, clear

. asdoc tabstat j_total_comp_w dlog_tdc1_w log_asset_w log_rev_w debtat_w coi whistle audit_cmte bd_ind_w family, by(ny) columns(stats) dec(3) label save(Output\T1D.doc) replace

             | j_total~w  dlog_td~w  log_ass~w  log_rev_w   debtat_w        coi    whistle  audit_c~e   bd_ind_w     family 
-------------+-------------------------------------------------------------------------------------------------------------
           0 |  621.3843    .027269   4.222948    3.54736   .3726277   .9514808   .8909893   .9495904   .8753319   .2291835 
           1 |  626.2282    .024432   4.253515   3.571511   .3781789   .9462049   .8997789    .944731   .8831938   .2505527 
(file Output\T1D.doc not found)
Click to Open File:  Output\T1D.doc

. 
. reg j_total_comp_w ny, cluster(ein) 

Linear regression                               Number of obs     =     12,466
                                                F(1, 9368)        =       0.04
                                                Prob > F          =     0.8324
                                                R-squared         =     0.0000
                                                Root MSE          =     705.74

                                (Std. err. adjusted for 9,369 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
j_total_co~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ny |   4.843826   22.88488     0.21   0.832    -40.01551    49.70316
       _cons |   621.3843   7.932676    78.33   0.000     605.8346    636.9341
------------------------------------------------------------------------------

. reg dlog_tdc1_w ny, cluster(ein)

Linear regression                               Number of obs     =     10,498
                                                F(1, 7946)        =       0.27
                                                Prob > F          =     0.6040
                                                R-squared         =     0.0000
                                                Root MSE          =     .19657

                                (Std. err. adjusted for 7,947 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
 dlog_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ny |  -.0028369   .0054701    -0.52   0.604    -.0135597    .0078858
       _cons |    .027269   .0018607    14.65   0.000     .0236214    .0309165
------------------------------------------------------------------------------

. reg log_asset_w ny, cluster(ein)

Linear regression                               Number of obs     =     12,466
                                                F(1, 9368)        =       0.36
                                                Prob > F          =     0.5471
                                                R-squared         =     0.0000
                                                Root MSE          =     1.4974

                                (Std. err. adjusted for 9,369 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
 log_asset_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ny |   .0305665   .0507624     0.60   0.547    -.0689389    .1300718
       _cons |   4.222948    .017354   243.34   0.000     4.188931    4.256966
------------------------------------------------------------------------------

. reg log_rev_w ny, cluster(ein)

Linear regression                               Number of obs     =     12,464
                                                F(1, 9366)        =       0.22
                                                Prob > F          =     0.6374
                                                R-squared         =     0.0000
                                                Root MSE          =     1.5068

                                (Std. err. adjusted for 9,367 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
   log_rev_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ny |    .024151   .0512323     0.47   0.637    -.0762754    .1245775
       _cons |    3.54736   .0171015   207.43   0.000     3.513837    3.580883
------------------------------------------------------------------------------

. reg debtat_w ny, cluster(ein)

Linear regression                               Number of obs     =     12,466
                                                F(1, 9368)        =       0.24
                                                Prob > F          =     0.6250
                                                R-squared         =     0.0000
                                                Root MSE          =     .32727

                                (Std. err. adjusted for 9,369 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
    debtat_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ny |   .0055512    .011356     0.49   0.625    -.0167089    .0278114
       _cons |   .3726277    .003709   100.47   0.000     .3653572    .3798982
------------------------------------------------------------------------------

. reg coi ny, cluster(ein)

Linear regression                               Number of obs     =     12,466
                                                F(1, 9368)        =       0.58
                                                Prob > F          =     0.4446
                                                R-squared         =     0.0001
                                                Root MSE          =     .21607

                                (Std. err. adjusted for 9,369 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
         coi | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ny |  -.0052759   .0069018    -0.76   0.445    -.0188049    .0082531
       _cons |   .9514808   .0023142   411.15   0.000     .9469445    .9560171
------------------------------------------------------------------------------

. reg whistle ny, cluster(ein)

Linear regression                               Number of obs     =     12,466
                                                F(1, 9368)        =       0.86
                                                Prob > F          =     0.3544
                                                R-squared         =     0.0001
                                                Root MSE          =     .31046

                                (Std. err. adjusted for 9,369 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
     whistle | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ny |   .0087896   .0094911     0.93   0.354    -.0098151    .0273943
       _cons |   .8909893   .0034464   258.53   0.000     .8842336    .8977449
------------------------------------------------------------------------------

. reg audit_cmte ny, cluster(ein)

Linear regression                               Number of obs     =     12,466
                                                F(1, 9368)        =       0.46
                                                Prob > F          =     0.4995
                                                R-squared         =     0.0000
                                                Root MSE          =     .21988

                                (Std. err. adjusted for 9,369 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
  audit_cmte | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ny |  -.0048594   .0071966    -0.68   0.500    -.0189663    .0092475
       _cons |   .9495904   .0024057   394.72   0.000     .9448747    .9543061
------------------------------------------------------------------------------

. reg bd_ind_w ny, cluster(ein)

Linear regression                               Number of obs     =     11,913
                                                F(1, 8949)        =       0.50
                                                Prob > F          =     0.4799
                                                R-squared         =     0.0000
                                                Root MSE          =     .76671

                                (Std. err. adjusted for 8,950 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
    bd_ind_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ny |   .0078619   .0111269     0.71   0.480    -.0139494    .0296732
       _cons |   .8753319   .0079624   109.93   0.000     .8597238      .89094
------------------------------------------------------------------------------

. reg family ny, cluster(ein)

Linear regression                               Number of obs     =     12,466
                                                F(1, 9368)        =       2.08
                                                Prob > F          =     0.1493
                                                R-squared         =     0.0002
                                                Root MSE          =     .42178

                                (Std. err. adjusted for 9,369 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
      family | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ny |   .0213691   .0148161     1.44   0.149    -.0076735    .0504118
       _cons |   .2291835   .0047966    47.78   0.000     .2197811     .238586
------------------------------------------------------------------------------

. 
. *T2. Total Pay
. use ceo_apr22, clear

. set more off

. reghdfe log_tdc1_w gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =      21.28
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9312
                                                  Adj R-squared   =     0.9195
                                                  Within R-sq.    =     0.0002
Number of clusters (state)   =         53         Root MSE        =     0.2032

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0167575   .0036323    -4.61   0.000    -.0240463   -.0094688
       _cons |   6.036999   .0002235  2.7e+04   0.000      6.03655    6.037447
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T2.xls, replace tstat bracket excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N) lab
> el    
Output\T2.xls
dir : seeout

. reghdfe log_tdc1_w gov_law10 log_asset_w coi whistle audit_cmte, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,417
Absorbing 2 HDFE groups                           F(   5,     52) =      38.07
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9318
                                                  Adj R-squared   =     0.9201
                                                  Within R-sq.    =     0.0079
Number of clusters (state)   =         53         Root MSE        =     0.2024

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0162544   .0035683    -4.56   0.000    -.0234147    -.009094
 log_asset_w |   .0894893   .0094708     9.45   0.000     .0704848    .1084938
         coi |   .0021908    .012543     0.17   0.862    -.0229786    .0273601
     whistle |  -.0121879   .0061707    -1.98   0.054    -.0245703    .0001946
  audit_cmte |   .0156798   .0069104     2.27   0.027      .001813    .0295466
       _cons |   5.658443   .0376497   150.29   0.000     5.582893    5.733993
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12331           0       12331     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T2.xls, tstat bracket excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N) label
Output\T2.xls
dir : seeout

. reghdfe log_tdc1_w gov_law10 log_asset_w coi whistle audit_cmte log_rev_w debtat_w bd_ind_w family, abs(ein fyear2) cluster(state)
(dropped 1775 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,220
Absorbing 2 HDFE groups                           F(   9,     52) =      31.81
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9321
                                                  Adj R-squared   =     0.9205
                                                  Within R-sq.    =     0.0117
Number of clusters (state)   =         53         Root MSE        =     0.2020

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0161273   .0034593    -4.66   0.000    -.0230689   -.0091857
 log_asset_w |   .0702645   .0089937     7.81   0.000     .0522173    .0883116
         coi |   .0021939   .0126754     0.17   0.863    -.0232412    .0276289
     whistle |  -.0111404   .0062928    -1.77   0.083    -.0237677     .001487
  audit_cmte |   .0148744    .007015     2.12   0.039     .0007977    .0289511
   log_rev_w |   .0391037   .0054322     7.20   0.000     .0282032    .0500043
    debtat_w |   .0264394   .0112443     2.35   0.023     .0038761    .0490027
    bd_ind_w |  -.0825614   .0217927    -3.79   0.000    -.1262917   -.0388311
      family |   .0138926   .0066224     2.10   0.041     .0006038    .0271814
       _cons |   5.662344   .0437713   129.36   0.000      5.57451    5.750177
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12324           0       12324     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T2.xls, tstat bracket excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N) label
Output\T2.xls
dir : seeout

. 
. use both_apr22, clear

. set more off

. reghdfe log_tdc1_w gov_law_ceo, abs(firm_yr firm_ceo year_ceo) cluster(state)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =    450,771
Absorbing 3 HDFE groups                           F(   1,     52) =      37.30
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8028
                                                  Adj R-squared   =     0.7633
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.2985

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |  -.0197636   .0032359    -6.11   0.000    -.0262568   -.0132703
       _cons |   5.777168    .000021  2.7e+05   0.000     5.777126     5.77721
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     57057       57057           0    *|
    firm_ceo |     18155           0       18155     |
    year_ceo |        22           2          20     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T2.xls, tstat bracket excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y, CEO-Ind-Year FE, N) label
Output\T2.xls
dir : seeout

. reghdfe log_tdc1_w gov_law_ceo if (state=="PA" | state=="NJ" | state=="CT" | state=="MA" | state=="VT" | state=="NY"), abs(firm_yr firm_ceo year_ceo) cluster(state)
(dropped 5 singleton observations)
(MWFE estimator converged in 9 iterations)

HDFE Linear regression                            Number of obs   =    125,547
Absorbing 3 HDFE groups                           F(   1,      5) =      15.38
Statistics robust to heteroskedasticity           Prob > F        =     0.0112
                                                  R-squared       =     0.8246
                                                  Adj R-squared   =     0.7903
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =          6         Root MSE        =     0.2773

                                  (Std. err. adjusted for 6 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |   -.023786   .0060662    -3.92   0.011    -.0393796   -.0081925
       _cons |   5.764256   .0001414  4.1e+04   0.000     5.763892     5.76462
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     15723       15723           0    *|
    firm_ceo |      4831           0        4831     |
    year_ceo |        22           2          20     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T2.xls, tstat bracket excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y, CEO-Ind-Year FE, N) label
Output\T2.xls
dir : seeout

. reghdfe log_tdc1_w gov_law_ceo, abs(firm_yr firm_ceo ceo_yr_ind) cluster(state)
(dropped 4 singleton observations)
(MWFE estimator converged in 55 iterations)

HDFE Linear regression                            Number of obs   =    450,767
Absorbing 3 HDFE groups                           F(   1,     52) =      41.88
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8028
                                                  Adj R-squared   =     0.7630
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.2986

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |  -.0233495   .0036083    -6.47   0.000    -.0305899    -.016109
       _cons |   5.777195   .0000234  2.5e+05   0.000     5.777148    5.777242
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     57055       57055           0    *|
    firm_ceo |     18155           0       18155     |
  ceo_yr_ind |       547           3         544     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T2.xls, tstat bracket excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, N, CEO-Ind-Year FE, Y) label
Output\T2.xls
dir : seeout

. 
. *T3.A
. use ceo_apr22, clear

. set more off

. reghdfe log_salary_w gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =       7.80
Statistics robust to heteroskedasticity           Prob > F        =     0.0073
                                                  R-squared       =     0.8140
                                                  Adj R-squared   =     0.7822
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.2872

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_salary_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0111882   .0040056    -2.79   0.007    -.0192261   -.0031503
       _cons |   5.705659   .0002931  1.9e+04   0.000     5.705071    5.706247
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T3A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   replace
Output\T3A.xls
dir : seeout

. reghdfe log_bonus_w gov_law10, abs(ein fyear2) cluster(state)
(dropped 1778 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,419
Absorbing 2 HDFE groups                           F(   1,     52) =       2.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0929
                                                  R-squared       =     0.7524
                                                  Adj R-squared   =     0.7100
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     1.2490

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
 log_bonus_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0341337   .0199392    -1.71   0.093    -.0741445    .0058772
       _cons |   1.938553    .001038  1867.54   0.000      1.93647    1.940636
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T3A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   
Output\T3A.xls
dir : seeout

. reghdfe log_perq_w gov_law10, abs(ein fyear2) cluster(state)
(dropped 1780 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,344
Absorbing 2 HDFE groups                           F(   1,     52) =      18.19
Statistics robust to heteroskedasticity           Prob > F        =     0.0001
                                                  R-squared       =     0.7201
                                                  Adj R-squared   =     0.6722
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     1.1401

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_perq_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0729624   .0171075    -4.26   0.000    -.1072912   -.0386336
       _cons |    1.66024   .0007807  2126.71   0.000     1.658673    1.661806
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12328           0       12328     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T3A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   
Output\T3A.xls
dir : seeout

. reghdfe log_defer_w gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,367
Absorbing 2 HDFE groups                           F(   1,     52) =       8.89
Statistics robust to heteroskedasticity           Prob > F        =     0.0044
                                                  R-squared       =     0.7020
                                                  Adj R-squared   =     0.6509
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     0.9787

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
 log_defer_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0711559   .0238713    -2.98   0.004    -.1190573   -.0232545
       _cons |   2.596163    .001143  2271.34   0.000     2.593869    2.598457
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12331           0       12331     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T3A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   
Output\T3A.xls
dir : seeout

. reghdfe log_nontax_w gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,416
Absorbing 2 HDFE groups                           F(   1,     52) =       1.45
Statistics robust to heteroskedasticity           Prob > F        =     0.2347
                                                  R-squared       =     0.6701
                                                  Adj R-squared   =     0.6136
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.7168

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_nontax_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0154398   .0128407    -1.20   0.235    -.0412066    .0103269
       _cons |   2.550506   .0006301  4048.00   0.000     2.549241     2.55177
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T3A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   
Output\T3A.xls
dir : seeout

. 
. *T3.B
. use ceo_apr22, clear

. set more off

. reghdfe bon_dum25k gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =      10.38
Statistics robust to heteroskedasticity           Prob > F        =     0.0022
                                                  R-squared       =     0.6948
                                                  Adj R-squared   =     0.6425
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.2840

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  bon_dum25k | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0116367   .0036118    -3.22   0.002    -.0188842   -.0043891
       _cons |   .3441919   .0001831  1879.70   0.000     .3438244    .3445593
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T3B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) replace
Output\T3B.xls
dir : seeout

. reghdfe bon_dum50k gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =      15.34
Statistics robust to heteroskedasticity           Prob > F        =     0.0003
                                                  R-squared       =     0.7154
                                                  Adj R-squared   =     0.6667
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     0.2537

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  bon_dum50k | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0167328    .004272    -3.92   0.000    -.0253052   -.0081605
       _cons |   .2623132   .0002201  1191.52   0.000     .2618714    .2627549
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T3B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   
Output\T3B.xls
dir : seeout

. reghdfe bon_dum75k gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =       8.08
Statistics robust to heteroskedasticity           Prob > F        =     0.0064
                                                  R-squared       =     0.7277
                                                  Adj R-squared   =     0.6811
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.2324

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  bon_dum75k | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0104302   .0036703    -2.84   0.006    -.0177951   -.0030652
       _cons |    .216384   .0001918  1128.02   0.000     .2159991    .2167689
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T3B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   
Output\T3B.xls
dir : seeout

. 
. *T4
. use ceo_apr22, clear

. set more off

. reghdfe avg_hrs_per_wk_c gov_law10, abs(ein fyear2) cluster(state)
(dropped 3401 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     49,909
Absorbing 2 HDFE groups                           F(   1,     52) =      43.09
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8191
                                                  Adj R-squared   =     0.7729
                                                  Within R-sq.    =     0.0002
Number of clusters (state)   =         53         Root MSE        =     3.7725

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~c | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |    .427463   .0651168     6.56   0.000     .2967966    .5581294
       _cons |   44.77336   .0040896  1.1e+04   0.000     44.76516    44.78157
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     10160           0       10160     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T4.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N) repla
> ce     
Output\T4.xls
dir : seeout

. reghdfe avg_hrs_per_wk_c gov_law10 log_asset_w coi whistle audit_cmte, abs(ein fyear2) cluster(state)
(dropped 3402 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     49,904
Absorbing 2 HDFE groups                           F(   5,     52) =      14.92
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8195
                                                  Adj R-squared   =     0.7733
                                                  Within R-sq.    =     0.0024
Number of clusters (state)   =         53         Root MSE        =     3.7687

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~c | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .4513988   .0654721     6.89   0.000     .3200194    .5827783
 log_asset_w |   .3068362   .1825798     1.68   0.099    -.0595371    .6732094
         coi |  -.4610413   .3704966    -1.24   0.219    -1.204497    .2824146
     whistle |  -.4365259   .1963621    -2.22   0.031    -.8305554   -.0424964
  audit_cmte |   .7717883   .1558316     4.95   0.000     .4590893    1.084487
       _cons |   43.65496   .8487439    51.43   0.000     41.95183    45.35809
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     10158           0       10158     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T4.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N)
Output\T4.xls
dir : seeout

. reghdfe avg_hrs_per_wk_c gov_law10 log_asset_w coi whistle audit_cmte log_rev_w debtat_w bd_ind_w family, abs(ein fyear2) cluster(state)
(dropped 3406 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     49,729
Absorbing 2 HDFE groups                           F(   9,     52) =       9.42
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8200
                                                  Adj R-squared   =     0.7738
                                                  Within R-sq.    =     0.0033
Number of clusters (state)   =         53         Root MSE        =     3.7666

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~c | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .4441644   .0659062     6.74   0.000     .3119139    .5764149
 log_asset_w |   .2924335   .1832472     1.60   0.117    -.0752789    .6601459
         coi |  -.5112402   .3682009    -1.39   0.171    -1.250089     .227609
     whistle |  -.4096793   .2001562    -2.05   0.046    -.8113221   -.0080364
  audit_cmte |   .7512649   .1599564     4.70   0.000     .4302888    1.072241
   log_rev_w |   .0270081   .0931521     0.29   0.773    -.1599153    .2139315
    debtat_w |  -.2505774   .2628049    -0.95   0.345     -.777934    .2767793
    bd_ind_w |  -1.223463    .375958    -3.25   0.002    -1.977878   -.4690485
      family |   .1204577   .1429688     0.84   0.403    -.1664301    .4073456
       _cons |    44.8194   .9059472    49.47   0.000     43.00149    46.63732
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     10134           0       10134     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T4.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N)     
Output\T4.xls
dir : seeout

. 
. use both_apr22, clear

. set more off

. reghdfe avg_hrs_per_wk_w gov_law_ceo, abs(firm_yr firm_ceo year_ceo) cluster(state)
(dropped 1536 singleton observations)
(MWFE estimator converged in 10 iterations)

HDFE Linear regression                            Number of obs   =    175,362
Absorbing 3 HDFE groups                           F(   1,     52) =      26.61
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7153
                                                  Adj R-squared   =     0.6475
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     4.5529

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |    .465245   .0901861     5.16   0.000     .2842734    .6462165
       _cons |   45.31764   .0005091  8.9e+04   0.000     45.31662    45.31866
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     22710       22710           0    *|
    firm_ceo |     11012           0       11012     |
    year_ceo |        22           2          20     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T4.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y, CEO-Ind-Year FE, N) 
Output\T4.xls
dir : seeout

. reghdfe avg_hrs_per_wk_w gov_law_ceo if (state=="PA" | state=="NJ" | state=="CT" | state=="MA" | state=="VT" | state=="NY"), abs(firm_yr firm_ceo year_ceo) cluster(state)
(dropped 447 singleton observations)
(MWFE estimator converged in 10 iterations)

HDFE Linear regression                            Number of obs   =     44,796
Absorbing 3 HDFE groups                           F(   1,      5) =       6.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0552
                                                  R-squared       =     0.7420
                                                  Adj R-squared   =     0.6820
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =          6         Root MSE        =     4.7073

                                  (Std. err. adjusted for 6 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |   .5009205   .2012491     2.49   0.055    -.0164067    1.018248
       _cons |   45.55328   .0044431  1.0e+04   0.000     45.54186     45.5647
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |      5703        5703           0    *|
    firm_ceo |      2729           0        2729     |
    year_ceo |        22           2          20     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T4.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y, CEO-Ind-Year FE, N)
Output\T4.xls
dir : seeout

. reghdfe avg_hrs_per_wk_w gov_law_ceo, abs(firm_yr firm_ceo ceo_yr_ind) cluster(state)
(dropped 1547 singleton observations)
(MWFE estimator converged in 79 iterations)

HDFE Linear regression                            Number of obs   =    175,351
Absorbing 3 HDFE groups                           F(   1,     52) =      29.35
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7157
                                                  Adj R-squared   =     0.6466
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     4.5582

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |   .5234389   .0966136     5.42   0.000     .3295696    .7173082
       _cons |   45.31721   .0005455  8.3e+04   0.000     45.31612    45.31831
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     22706       22706           0    *|
    firm_ceo |     11012           0       11012     |
  ceo_yr_ind |       537           6         531     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T4.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, N, CEO-Ind-Year FE, Y)
Output\T4.xls
dir : seeout

. 
. *T5
. use ceo_apr22, clear

. set more off

. reghdfe log_grnt_contrib_w gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =      19.99
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9383
                                                  Adj R-squared   =     0.9278
                                                  Within R-sq.    =     0.0003
Number of clusters (state)   =         53         Root MSE        =     0.3874

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_grnt_c~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0429689   .0096109     4.47   0.000     .0236832    .0622545
       _cons |   1.381638    .000457  3023.51   0.000     1.380721    1.382555
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T5.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)  replace
Output\T5.xls
dir : seeout

. reghdfe log_grnt_contrib_w gov_law10 log_asset_w coi whistle audit_cmte, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,417
Absorbing 2 HDFE groups                           F(   5,     52) =      45.09
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9399
                                                  Adj R-squared   =     0.9296
                                                  Within R-sq.    =     0.0260
Number of clusters (state)   =         53         Root MSE        =     0.3824

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_grnt_c~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0433051   .0085722     5.05   0.000     .0261036    .0605065
 log_asset_w |   .3154665   .0259658    12.15   0.000     .2633624    .3675707
         coi |  -.0367787   .0151843    -2.42   0.019    -.0672484   -.0063091
     whistle |   .0162366   .0158577     1.02   0.311    -.0155842    .0480575
  audit_cmte |   .0058581   .0099437     0.59   0.558    -.0140955    .0258117
       _cons |    .083291    .117134     0.71   0.480    -.1517555    .3183376
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12331           0       12331     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T5.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)  
Output\T5.xls
dir : seeout

. reghdfe log_grnt_contrib_w gov_law10 if coi_whistle_audit==1, abs(ein fyear2) cluster(state)
(dropped 90 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     63,507
Absorbing 2 HDFE groups                           F(   1,     52) =      25.38
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9379
                                                  Adj R-squared   =     0.9288
                                                  Within R-sq.    =     0.0005
Number of clusters (state)   =         53         Root MSE        =     0.3942

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_grnt_c~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0540331   .0107263     5.04   0.000     .0325092    .0755571
       _cons |   1.531169   .0004987  3070.33   0.000     1.530168     1.53217
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      8072           0        8072     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T5.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)  
Output\T5.xls
dir : seeout

. reghdfe log_volunteer2_w gov_law10 , a(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =      23.74
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9294
                                                  Adj R-squared   =     0.9173
                                                  Within R-sq.    =     0.0002
Number of clusters (state)   =         53         Root MSE        =     0.3187

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_volunt~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0259644   .0053294     4.87   0.000     .0152702    .0366587
       _cons |   .8634016   .0003268  2642.04   0.000     .8627458    .8640573
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T5.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)    
Output\T5.xls
dir : seeout

. reghdfe log_volunteer2_w gov_law10 log_asset_w coi whistle audit_cmte, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,417
Absorbing 2 HDFE groups                           F(   5,     52) =       9.91
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9295
                                                  Adj R-squared   =     0.9174
                                                  Within R-sq.    =     0.0014
Number of clusters (state)   =         53         Root MSE        =     0.3185

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_volunt~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0253368   .0052615     4.82   0.000     .0147789    .0358947
 log_asset_w |   .0477546   .0094364     5.06   0.000      .028819    .0666902
         coi |   .0013137    .017353     0.08   0.940    -.0335076     .036135
     whistle |   .0394236   .0176465     2.23   0.030     .0040132    .0748339
  audit_cmte |   .0135929   .0075993     1.79   0.079    -.0016562    .0288419
       _cons |   .6163821   .0427841    14.41   0.000     .5305295    .7022347
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12331           0       12331     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T5.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)    
Output\T5.xls
dir : seeout

. reghdfe log_volunteer2_w gov_law10 if coi_whistle_audit==1, abs(ein fyear2) cluster(state)
(dropped 90 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     63,507
Absorbing 2 HDFE groups                           F(   1,     52) =      11.15
Statistics robust to heteroskedasticity           Prob > F        =     0.0016
                                                  R-squared       =     0.9257
                                                  Adj R-squared   =     0.9149
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     0.3351

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_volunt~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0235801   .0070609     3.34   0.002     .0094112    .0377489
       _cons |   .9824225   .0004238  2318.27   0.000     .9815721    .9832729
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      8072           0        8072     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T5.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)    
Output\T5.xls
dir : seeout

. 
. *T6
. use ceo_apr22, clear

. set more off

. reghdfe log_tdc1_w law_grnt ny_grnt post_grnt log_grnt_contrib_w, abs(year_ny firm_post) cluster(state)
(dropped 3538 singleton observations)
(MWFE estimator converged in 13 iterations)

HDFE Linear regression                            Number of obs   =     82,662
Absorbing 2 HDFE groups                           F(   4,     52) =      80.50
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9526
                                                  Adj R-squared   =     0.9370
                                                  Within R-sq.    =     0.0003
Number of clusters (state)   =         53         Root MSE        =     0.1789

                                       (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------------
                   |               Robust
        log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
          law_grnt |   .0238187   .0058926     4.04   0.000     .0119944     .035643
           ny_grnt |  -.0026117   .0042616    -0.61   0.543    -.0111633    .0059399
         post_grnt |   .0016979   .0059133     0.29   0.775     -.010168    .0135637
log_grnt_contrib_w |   .0069922   .0040189     1.74   0.088    -.0010723    .0150568
             _cons |   6.024644   .0035813  1682.26   0.000     6.017458    6.031831
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     year_ny |        22           0          22     |
   firm_post |     20425           2       20423     |
-----------------------------------------------------+

. outreg2 using Output\T6.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm-Pre/Post FE, Y, Year-NY FE, Y)    replace
Output\T6.xls
dir : seeout

. reghdfe log_tdc1_w llaw_grnt lny_grnt lpost_grnt llog_grnt_contrib_w, abs(year_ny firm_post) cluster(state)
(dropped 3263 singleton observations)
(MWFE estimator converged in 14 iterations)

HDFE Linear regression                            Number of obs   =     66,030
Absorbing 2 HDFE groups                           F(   4,     52) =      39.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9614
                                                  Adj R-squared   =     0.9475
                                                  Within R-sq.    =     0.0007
Number of clusters (state)   =         53         Root MSE        =     0.1577

                                        (Std. err. adjusted for 53 clusters in state)
-------------------------------------------------------------------------------------
                    |               Robust
         log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          llaw_grnt |   .0180356   .0049349     3.65   0.001      .008133    .0279382
           lny_grnt |  -.0046301   .0045857    -1.01   0.317    -.0138319    .0045717
         lpost_grnt |   -.007291   .0047507    -1.53   0.131    -.0168239     .002242
llog_grnt_contrib_w |    .014083   .0040529     3.47   0.001     .0059503    .0222157
              _cons |   6.034523   .0037496  1609.40   0.000     6.026999    6.042047
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     year_ny |        20           0          20     |
   firm_post |     17396           2       17394     |
-----------------------------------------------------+

. outreg2 using Output\T6.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm-Pre/Post FE, Y, Year-NY FE, Y)    
Output\T6.xls
dir : seeout

. reghdfe log_tdc1_w law_vol ny_vol post_vol log_volunteer2_w, abs(year_ny firm_post) cluster(state)
(dropped 3538 singleton observations)
(MWFE estimator converged in 13 iterations)

HDFE Linear regression                            Number of obs   =     82,662
Absorbing 2 HDFE groups                           F(   4,     52) =     101.96
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9526
                                                  Adj R-squared   =     0.9370
                                                  Within R-sq.    =     0.0003
Number of clusters (state)   =         53         Root MSE        =     0.1789

                                     (Std. err. adjusted for 53 clusters in state)
----------------------------------------------------------------------------------
                 |               Robust
      log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
         law_vol |   .0490654    .009641     5.09   0.000     .0297194    .0684114
          ny_vol |   .0029609   .0051391     0.58   0.567    -.0073515    .0132732
        post_vol |  -.0058587   .0081357    -0.72   0.475    -.0221841    .0104668
log_volunteer2_w |   .0061988   .0053083     1.17   0.248     -.004453    .0168507
           _cons |   6.031611   .0029189  2066.43   0.000     6.025754    6.037468
----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     year_ny |        22           0          22     |
   firm_post |     20425           2       20423     |
-----------------------------------------------------+

. outreg2 using Output\T6.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm-Pre/Post FE, Y, Year-NY FE, Y)      
Output\T6.xls
dir : seeout

. reghdfe log_tdc1_w llaw_vol lny_vol lpost_vol llog_volunteer2_w, abs(year_ny firm_post) cluster(state)
(dropped 3263 singleton observations)
(MWFE estimator converged in 13 iterations)

HDFE Linear regression                            Number of obs   =     66,030
Absorbing 2 HDFE groups                           F(   4,     52) =      48.72
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9614
                                                  Adj R-squared   =     0.9475
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     0.1578

                                      (Std. err. adjusted for 53 clusters in state)
-----------------------------------------------------------------------------------
                  |               Robust
       log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
         llaw_vol |  -.0066952   .0081509    -0.82   0.415    -.0230511    .0096607
          lny_vol |   .0149722    .005631     2.66   0.010     .0036727    .0262717
        lpost_vol |   .0081486   .0089978     0.91   0.369    -.0099067     .026204
llog_volunteer2_w |   .0001158   .0058643     0.02   0.984    -.0116518    .0118833
            _cons |   6.045651   .0030477  1983.69   0.000     6.039536    6.051767
-----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     year_ny |        20           0          20     |
   firm_post |     17396           2       17394     |
-----------------------------------------------------+

. outreg2 using Output\T6.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm-Pre/Post FE, Y, Year-NY FE, Y)      
Output\T6.xls
dir : seeout

. 
. *T7
. use ceo_apr22, clear

. set more off

. reghdfe comp_cmte_fill gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =      15.32
Statistics robust to heteroskedasticity           Prob > F        =     0.0003
                                                  R-squared       =     0.8494
                                                  Adj R-squared   =     0.8237
                                                  Within R-sq.    =     0.0002
Number of clusters (state)   =         53         Root MSE        =     0.2086

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
comp_cmte_~l | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0182009   .0046495     3.91   0.000      .008871    .0275309
       _cons |   .5564087   .0002376  2341.48   0.000     .5559319    .5568856
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T7.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   replace
Output\T7.xls
dir : seeout

. reghdfe consultant_fill gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =      10.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0018
                                                  R-squared       =     0.8489
                                                  Adj R-squared   =     0.8230
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     0.1901

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
consultant~l | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0119349   .0036222     3.29   0.002     .0046664    .0192034
       _cons |   .2853061   .0002097  1360.45   0.000     .2848852    .2857269
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T7.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   
Output\T7.xls
dir : seeout

. reghdfe employ_cntrct_fill gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =      18.78
Statistics robust to heteroskedasticity           Prob > F        =     0.0001
                                                  R-squared       =     0.8494
                                                  Adj R-squared   =     0.8236
                                                  Within R-sq.    =     0.0002
Number of clusters (state)   =         53         Root MSE        =     0.1971

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
employ_cnt~l | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0181249   .0041829     4.33   0.000     .0097313    .0265184
       _cons |   .3266826   .0002302  1419.14   0.000     .3262207    .3271446
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T7.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   
Output\T7.xls
dir : seeout

. reghdfe oth_firms990_fill gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =       5.00
Statistics robust to heteroskedasticity           Prob > F        =     0.0296
                                                  R-squared       =     0.8251
                                                  Adj R-squared   =     0.7951
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     0.2148

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
oth_firms9~l | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0140516   .0062823     2.24   0.030     .0014453     .026658
       _cons |   .6569531   .0003345  1963.82   0.000     .6562818    .6576243
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T7.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   
Output\T7.xls
dir : seeout

. reghdfe compceo_process gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =      10.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0025
                                                  R-squared       =     0.7964
                                                  Adj R-squared   =     0.7615
                                                  Within R-sq.    =     0.0003
Number of clusters (state)   =         53         Root MSE        =     0.1488

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
compceo_pr~s | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0165119   .0051946     3.18   0.002     .0060881    .0269357
       _cons |   .8957501    .000258  3472.00   0.000     .8952324    .8962678
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T7.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)   
Output\T7.xls
dir : seeout

. 
. *T8.A
. use ceo_apr22, clear

. reghdfe log_tdc1_w gov_law10 if charity50==0, abs(ein fyear2) cluster(state)
(dropped 47 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     52,008
Absorbing 2 HDFE groups                           F(   1,     52) =      22.45
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9286
                                                  Adj R-squared   =     0.9185
                                                  Within R-sq.    =     0.0002
Number of clusters (state)   =         53         Root MSE        =     0.2064

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0190116   .0040128    -4.74   0.000    -.0270638   -.0109593
       _cons |    6.13133   .0002149  2.9e+04   0.000     6.130899    6.131761
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      6415           0        6415     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T8A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N) replace
Output\T8A.xls
dir : seeout

. 
. use both_apr22, clear

. reghdfe log_tdc1_w gov_law_ceo if charity50==0, abs(firm_yr firm_ceo fyear2#ceo) cluster(state)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =    320,564
Absorbing 3 HDFE groups                           F(   1,     52) =      38.37
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8064
                                                  Adj R-squared   =     0.7704
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.3007

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |  -.0283447   .0045757    -6.19   0.000    -.0375264    -.019163
       _cons |   5.816109   .0000243  2.4e+05   0.000      5.81606    5.816157
------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
      firm_yr |     39021       39021           0    *|
     firm_ceo |     11143           0       11143     |
   fyear2#ceo |        22           2          20     |
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T8A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y)
Output\T8A.xls
dir : seeout

. 
. use ceo_apr22, clear

. reghdfe log_tdc1_w gov_law10 if charity50==1, abs(ein fyear2) cluster(state)
(dropped 40 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     19,090
Absorbing 2 HDFE groups                           F(   1,     51) =       1.22
Statistics robust to heteroskedasticity           Prob > F        =     0.2745
                                                  R-squared       =     0.9173
                                                  Adj R-squared   =     0.9056
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         52         Root MSE        =     0.1818

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0055339   .0050101    -1.10   0.275    -.0155921    .0045244
       _cons |   5.856239   .0003288  1.8e+04   0.000     5.855579    5.856899
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      2359           0        2359     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T8A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N) 
Output\T8A.xls
dir : seeout

. 
. use both_apr22, clear

. reghdfe log_tdc1_w gov_law_ceo if charity50==1, abs(firm_yr firm_ceo fyear2#ceo) cluster(state)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     85,289
Absorbing 3 HDFE groups                           F(   1,     51) =       0.44
Statistics robust to heteroskedasticity           Prob > F        =     0.5089
                                                  R-squared       =     0.7992
                                                  Adj R-squared   =     0.7532
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         52         Root MSE        =     0.2489

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |  -.0040953   .0061555    -0.67   0.509    -.0164531    .0082625
       _cons |   5.606378   .0000621  9.0e+04   0.000     5.606253    5.606502
------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
      firm_yr |     12277       12277           0    *|
     firm_ceo |      3614           0        3614     |
   fyear2#ceo |        22           2          20     |
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T8A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y)
Output\T8A.xls
dir : seeout

. 
. *T8.B
. use female_apr22, clear

. reghdfe log_tdc1_w gov_law10  if ceo==1 & female2_2013==0  , a(ein fyear2) cluster(state)
(dropped 38 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     45,014
Absorbing 2 HDFE groups                           F(   1,     51) =      53.79
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9268
                                                  Adj R-squared   =     0.9193
                                                  Within R-sq.    =     0.0006
Number of clusters (state)   =         52         Root MSE        =     0.2211

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0369209   .0050341    -7.33   0.000    -.0470274   -.0268145
       _cons |   6.382295   .0002302  2.8e+04   0.000     6.381833    6.382757
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      4171           0        4171     |
      fyear2 |        10           1           9     |
-----------------------------------------------------+

. outreg2 using Output\T8B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N) replace
Output\T8B.xls
dir : seeout

. reghdfe log_tdc1_w gov_law_ceo  if female2_2013==0 , a(ein#fyear2 ein#ceo ceo#fyear2) cluster(state)
(dropped 4242 singleton observations)
(MWFE estimator converged in 26 iterations)

HDFE Linear regression                            Number of obs   =    249,163
Absorbing 3 HDFE groups                           F(   1,     52) =       5.95
Statistics robust to heteroskedasticity           Prob > F        =     0.0182
                                                  R-squared       =     0.8560
                                                  Adj R-squared   =     0.8321
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.2736

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |  -.0146817    .006021    -2.44   0.018    -.0267638   -.0025996
       _cons |    5.86055    .000039  1.5e+05   0.000     5.860472    5.860628
------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
   ein#fyear2 |     27706       27706           0    *|
      ein#ceo |      7670           0        7670     |
   ceo#fyear2 |        20           2          18     |
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T8B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y)
Output\T8B.xls
dir : seeout

. reghdfe log_tdc1_w gov_law10  if ceo==1 & female2_2013==1  , a(ein fyear2) cluster(state)
(dropped 13 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     21,796
Absorbing 2 HDFE groups                           F(   1,     51) =       0.01
Statistics robust to heteroskedasticity           Prob > F        =     0.9194
                                                  R-squared       =     0.9503
                                                  Adj R-squared   =     0.9472
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         52         Root MSE        =     0.1906

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0016335   .0160549     0.10   0.919    -.0305981    .0338652
       _cons |   6.643997    .000426  1.6e+04   0.000     6.643142    6.644853
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      1272           0        1272     |
      fyear2 |        10           1           9     |
-----------------------------------------------------+

. outreg2 using Output\T8B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N) 
Output\T8B.xls
dir : seeout

. reghdfe log_tdc1_w gov_law_ceo  if female2_2013==1 , a(ein#fyear2 ein#ceo ceo#fyear2) cluster(state)
(dropped 1708 singleton observations)
(MWFE estimator converged in 30 iterations)

HDFE Linear regression                            Number of obs   =     72,476
Absorbing 3 HDFE groups                           F(   1,     51) =       0.62
Statistics robust to heteroskedasticity           Prob > F        =     0.4340
                                                  R-squared       =     0.9218
                                                  Adj R-squared   =     0.9092
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         52         Root MSE        =     0.2375

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |   .0098145   .0124444     0.79   0.434    -.0151688    .0347977
       _cons |   5.969908   .0000967  6.2e+04   0.000     5.969714    5.970102
------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
   ein#fyear2 |      7789        7789           0    *|
      ein#ceo |      2251           0        2251     |
   ceo#fyear2 |        20           2          18     |
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T8B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y)
Output\T8B.xls
dir : seeout

. 
. *T9.A
. use ceo_apr22, clear

. reghdfe avg_hrs_per_wk_w gov_law10 if charity50==0, abs(ein fyear2) cluster(state)
(dropped 635 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     26,130
Absorbing 2 HDFE groups                           F(   1,     52) =      43.54
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8303
                                                  Adj R-squared   =     0.7939
                                                  Within R-sq.    =     0.0004
Number of clusters (state)   =         53         Root MSE        =     3.8041

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .5765777     .08738     6.60   0.000     .4012369    .7519184
       _cons |   45.89253   .0047102  9743.24   0.000     45.88308    45.90198
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      4609           0        4609     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T9A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) replace
Output\T9A.xls
dir : seeout

. reghdfe log_grnt_contrib_w gov_law10 if charity50==0, abs(ein fyear2) cluster(state)
(dropped 47 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     52,008
Absorbing 2 HDFE groups                           F(   1,     52) =       5.57
Statistics robust to heteroskedasticity           Prob > F        =     0.0221
                                                  R-squared       =     0.9076
                                                  Adj R-squared   =     0.8945
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     0.3724

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_grnt_c~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |    .024036   .0101855     2.36   0.022     .0035972    .0444747
       _cons |   .9709642    .000426  2279.23   0.000     .9701093     .971819
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      6415           0        6415     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T9A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) 
Output\T9A.xls
dir : seeout

. reghdfe log_volunteer2_w gov_law10 if charity50==0, abs(ein fyear2) cluster(state)
(dropped 47 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     52,008
Absorbing 2 HDFE groups                           F(   1,     52) =      21.00
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9174
                                                  Adj R-squared   =     0.9058
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     0.3059

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_volunt~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0239055   .0052169     4.58   0.000      .013437    .0343741
       _cons |   .8164162   .0001942  4204.28   0.000     .8160265    .8168059
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      6415           0        6415     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T9A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) 
Output\T9A.xls
dir : seeout

. reghdfe avg_hrs_per_wk_w gov_law10 if charity50==1, abs(ein fyear2) cluster(state)
(dropped 215 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     10,171
Absorbing 2 HDFE groups                           F(   1,     51) =       2.21
Statistics robust to heteroskedasticity           Prob > F        =     0.1434
                                                  R-squared       =     0.8435
                                                  Adj R-squared   =     0.8111
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         52         Root MSE        =     3.3131

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .1779961   .1197792     1.49   0.143    -.0624707    .4184629
       _cons |   44.01929   .0070572  6237.50   0.000     44.00512    44.03346
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      1731           0        1731     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T9A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) 
Output\T9A.xls
dir : seeout

. reghdfe log_grnt_contrib_w gov_law10 if charity50==1, abs(ein fyear2) cluster(state)
(dropped 40 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     19,090
Absorbing 2 HDFE groups                           F(   1,     51) =      42.89
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9338
                                                  Adj R-squared   =     0.9245
                                                  Within R-sq.    =     0.0013
Number of clusters (state)   =         52         Root MSE        =     0.4214

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_grnt_c~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |    .085196    .013009     6.55   0.000     .0590794    .1113125
       _cons |   2.599444   .0006876  3780.47   0.000     2.598063    2.600824
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      2359           0        2359     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T9A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) 
Output\T9A.xls
dir : seeout

. reghdfe log_volunteer2_w gov_law10 if charity50==1, abs(ein fyear2) cluster(state)
(dropped 40 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     19,090
Absorbing 2 HDFE groups                           F(   1,     51) =       1.81
Statistics robust to heteroskedasticity           Prob > F        =     0.1846
                                                  R-squared       =     0.9386
                                                  Adj R-squared   =     0.9299
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         52         Root MSE        =     0.3649

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_volunt~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0143281   .0106529     1.35   0.185    -.0070584    .0357146
       _cons |   1.073889   .0009972  1076.88   0.000     1.071887    1.075891
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      2359           0        2359     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\T9A.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) 
Output\T9A.xls
dir : seeout

. 
. *T9.B
. use female_apr22, clear

. reghdfe avg_hrs_per_wk_w gov_law10    if ceo==1 & female2_2013==0 , a(ein fyear2) cluster(state)
(dropped 423 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     20,585
Absorbing 2 HDFE groups                           F(   1,     51) =       6.02
Statistics robust to heteroskedasticity           Prob > F        =     0.0176
                                                  R-squared       =     0.8374
                                                  Adj R-squared   =     0.8114
                                                  Within R-sq.    =     0.0003
Number of clusters (state)   =         52         Root MSE        =     3.6352

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .5226307   .2130829     2.45   0.018     .0948489    .9504125
       _cons |    46.5708   .0080296  5799.85   0.000     46.55468    46.58692
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      2826           0        2826     |
      fyear2 |        10           1           9     |
-----------------------------------------------------+

. outreg2 using Output\T9B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) replace
Output\T9B.xls
dir : seeout

. reghdfe log_grnt_contrib_w gov_law10 if ceo==1 & female2_2013==0  , a(ein fyear2) cluster(state)
(dropped 38 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     45,014
Absorbing 2 HDFE groups                           F(   1,     51) =      34.31
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9452
                                                  Adj R-squared   =     0.9396
                                                  Within R-sq.    =     0.0008
Number of clusters (state)   =         52         Root MSE        =     0.3802

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_grnt_c~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0783712   .0133796     5.86   0.000     .0515105    .1052319
       _cons |   1.745031   .0008581  2033.62   0.000     1.743308    1.746754
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      4171           0        4171     |
      fyear2 |        10           1           9     |
-----------------------------------------------------+

. outreg2 using Output\T9B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)
Output\T9B.xls
dir : seeout

. reghdfe log_volunteer2_w gov_law10  if ceo==1  & female2_2013==0  , a(ein fyear2) cluster(state)
(dropped 38 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     45,014
Absorbing 2 HDFE groups                           F(   1,     51) =      13.38
Statistics robust to heteroskedasticity           Prob > F        =     0.0006
                                                  R-squared       =     0.9381
                                                  Adj R-squared   =     0.9318
                                                  Within R-sq.    =     0.0005
Number of clusters (state)   =         52         Root MSE        =     0.3288

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_volunt~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0514105   .0140563     3.66   0.001     .0231912    .0796297
       _cons |    1.13426   .0005823  1947.78   0.000     1.133091    1.135429
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      4171           0        4171     |
      fyear2 |        10           1           9     |
-----------------------------------------------------+

. outreg2 using Output\T9B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) 
Output\T9B.xls
dir : seeout

. reghdfe avg_hrs_per_wk_w gov_law10    if ceo==1 & female2_2013==1, a(ein fyear2) cluster(state)
(dropped 112 singleton observations)
(MWFE estimator converged in 9 iterations)

HDFE Linear regression                            Number of obs   =     10,151
Absorbing 2 HDFE groups                           F(   1,     50) =       2.00
Statistics robust to heteroskedasticity           Prob > F        =     0.1636
                                                  R-squared       =     0.7724
                                                  Adj R-squared   =     0.7495
                                                  Within R-sq.    =     0.0009
Number of clusters (state)   =         51         Root MSE        =     4.4514

                                 (Std. err. adjusted for 51 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -1.442375   1.020218    -1.41   0.164    -3.491543    .6067932
       _cons |   47.31081   .0243648  1941.77   0.000     47.26187    47.35975
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |       919           0         919     |
      fyear2 |        10           1           9     |
-----------------------------------------------------+

. outreg2 using Output\T9B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)
Output\T9B.xls
dir : seeout

. reghdfe log_grnt_contrib_w gov_law10 if ceo==1 & female2_2013==1 , a(ein fyear2) cluster(state)
(dropped 13 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     21,796
Absorbing 2 HDFE groups                           F(   1,     51) =       0.77
Statistics robust to heteroskedasticity           Prob > F        =     0.3857
                                                  R-squared       =     0.9037
                                                  Adj R-squared   =     0.8976
                                                  Within R-sq.    =     0.0004
Number of clusters (state)   =         52         Root MSE        =     0.4774

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_grnt_c~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0832447   .0951367    -0.88   0.386    -.2742396    .1077502
       _cons |    1.60489   .0025521   628.85   0.000     1.599767    1.610014
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      1272           0        1272     |
      fyear2 |        10           1           9     |
-----------------------------------------------------+

. outreg2 using Output\T9B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)
Output\T9B.xls
dir : seeout

. reghdfe log_volunteer2_w gov_law10  if ceo==1  & female2_2013==1  , a(ein fyear2) cluster(state)
(dropped 13 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     21,796
Absorbing 2 HDFE groups                           F(   1,     51) =      11.97
Statistics robust to heteroskedasticity           Prob > F        =     0.0011
                                                  R-squared       =     0.9641
                                                  Adj R-squared   =     0.9619
                                                  Within R-sq.    =     0.0007
Number of clusters (state)   =         52         Root MSE        =     0.2777

                                 (Std. err. adjusted for 52 clusters in state)
------------------------------------------------------------------------------
             |               Robust
log_volunt~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0623139   .0180114     3.46   0.001     .0261546    .0984732
       _cons |   1.204646   .0004838  2489.96   0.000     1.203675    1.205617
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      1272           0        1272     |
      fyear2 |        10           1           9     |
-----------------------------------------------------+

. outreg2 using Output\T9B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) 
Output\T9B.xls
dir : seeout

. 
. *T10.A
. use t2_panel, replace

. 
. asdoc tabstat j_total_comp_w dlog_tdc1_w log_asset_w femaleceo, by(charity50) stats(mean) dec(3) label save(Output\T10A_1.doc) replace

             | j_total~w  dlog_td~w  log_ass~w  femaleceo 
-------------+-------------------------------------------
           0 |  677.7782   .0259756   4.225512    .210448 
           1 |  448.4248   .0295909   4.275012   .2693319 
(file Output\T10A_1.doc not found)
Click to Open File:  Output\T10A_1.doc

. reg j_total_comp_w charity50, cluster(ein)

Linear regression                               Number of obs     =     11,887
                                                F(1, 8789)        =     268.95
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0217
                                                Root MSE          =     684.82

                                (Std. err. adjusted for 8,790 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
j_total_co~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   charity50 |  -229.3533   13.98516   -16.40   0.000    -256.7675   -201.9392
       _cons |   677.7782     9.5478    70.99   0.000     659.0622    696.4941
------------------------------------------------------------------------------

. reg dlog_tdc1_w charity50, cluster(ein)

Linear regression                               Number of obs     =     10,498
                                                F(1, 7946)        =       0.95
                                                Prob > F          =     0.3304
                                                R-squared         =     0.0001
                                                Root MSE          =     .19656

                                (Std. err. adjusted for 7,947 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
 dlog_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   charity50 |   .0036153   .0037144     0.97   0.330    -.0036659    .0108966
       _cons |   .0259756   .0021147    12.28   0.000     .0218302    .0301211
------------------------------------------------------------------------------

. reg log_asset_w charity50, cluster(ein)

Linear regression                               Number of obs     =     11,887
                                                F(1, 8789)        =       1.64
                                                Prob > F          =     0.2009
                                                R-squared         =     0.0002
                                                Root MSE          =     1.4997

                                (Std. err. adjusted for 8,790 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
 log_asset_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   charity50 |   .0495008   .0387018     1.28   0.201    -.0263639    .1253654
       _cons |   4.225512   .0194782   216.94   0.000      4.18733    4.263694
------------------------------------------------------------------------------

. reg femaleceo charity50, cluster(ein)

Linear regression                               Number of obs     =      7,280
                                                F(1, 5324)        =      17.11
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0038
                                                Root MSE          =     .41738

                                (Std. err. adjusted for 5,325 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
   femaleceo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   charity50 |   .0588839   .0142357     4.14   0.000     .0309761    .0867917
       _cons |    .210448   .0068357    30.79   0.000     .1970473    .2238488
------------------------------------------------------------------------------

. 
. asdoc tabstat j_total_comp_w dlog_tdc1_w log_asset_w  charity50, by(femaleceo) stats(mean) dec(3) label save(Output\T10A_2.doc) replace

             | j_total~w  dlog_td~w  log_ass~w  charity50 
-------------+-------------------------------------------
           0 |   649.898   .0293234   4.557654   .2464514 
           1 |  537.1355   .0302864   4.367718   .3114355 
(file Output\T10A_2.doc not found)
Click to Open File:  Output\T10A_2.doc

. reg j_total_comp_w femaleceo, cluster(ein)

Linear regression                               Number of obs     =      7,536
                                                F(1, 5580)        =      35.10
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0049
                                                Root MSE          =     670.69

                                (Std. err. adjusted for 5,581 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
j_total_co~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   femaleceo |  -112.7626   19.03214    -5.92   0.000     -150.073   -75.45217
       _cons |    649.898   10.57688    61.45   0.000     629.1632    670.6329
------------------------------------------------------------------------------

. reg dlog_tdc1_w femaleceo, cluster(ein)

Linear regression                               Number of obs     =      6,689
                                                F(1, 4967)        =       0.03
                                                Prob > F          =     0.8575
                                                R-squared         =     0.0000
                                                Root MSE          =     .20199

                                (Std. err. adjusted for 4,968 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
 dlog_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   femaleceo |    .000963    .005363     0.18   0.857    -.0095508    .0114769
       _cons |   .0293234   .0025758    11.38   0.000     .0242736    .0343732
------------------------------------------------------------------------------

. reg log_asset_w femaleceo, cluster(ein)

Linear regression                               Number of obs     =      7,536
                                                F(1, 5580)        =      17.38
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0031
                                                Root MSE          =     1.4259

                                (Std. err. adjusted for 5,581 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
 log_asset_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   femaleceo |   -.189936   .0455602    -4.17   0.000    -.2792516   -.1006203
       _cons |   4.557654   .0227806   200.07   0.000     4.512995    4.602313
------------------------------------------------------------------------------

. reg charity50 femaleceo, cluster(ein)

Linear regression                               Number of obs     =      7,280
                                                F(1, 5324)        =      17.10
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0038
                                                Root MSE          =     .43847

                                (Std. err. adjusted for 5,325 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
   charity50 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   femaleceo |   .0649841   .0157133     4.14   0.000     .0341796    .0957886
       _cons |   .2464514   .0070324    35.04   0.000     .2326649    .2602378
------------------------------------------------------------------------------

. 
. *T10.B
. use ceo_apr22, clear

. 
. reghdfe log_tdc1_w char50contemp, abs(ntee1_r#fyear2) cluster(ein)
(dropped 2 singleton observations)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =     86,198
Absorbing 1 HDFE group                            F(   1,  14110) =     193.98
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2788
                                                  Adj R-squared   =     0.2765
                                                  Within R-sq.    =     0.0126
Number of clusters (ein)     =     14,111         Root MSE        =     0.6103

                                (Std. err. adjusted for 14,111 clusters in ein)
-------------------------------------------------------------------------------
              |               Robust
   log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
char50contemp |  -.1807215   .0129758   -13.93   0.000    -.2061558   -.1552872
        _cons |   6.079401   .0064839   937.62   0.000     6.066691     6.09211
-------------------------------------------------------------------------------

Absorbed degrees of freedom:
----------------------------------------------------------+
      Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------+---------------------------------------|
   ntee1_r#fyear2 |       275           0         275     |
----------------------------------------------------------+

. outreg2 using Output\T10B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Industry-Year FE, Y) replace
Output\T10B.xls
dir : seeout

. reghdfe log_tdc1_w char50contemp log_asset_w coi whistle audit_cmte, abs(ntee1_r#fyear2) cluster(ein)
(dropped 2 singleton observations)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =     86,194
Absorbing 1 HDFE group                            F(   5,  14109) =    1250.26
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5019
                                                  Adj R-squared   =     0.5003
                                                  Within R-sq.    =     0.3180
Number of clusters (ein)     =     14,110         Root MSE        =     0.5072

                                (Std. err. adjusted for 14,110 clusters in ein)
-------------------------------------------------------------------------------
              |               Robust
   log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
char50contemp |  -.1934687   .0111466   -17.36   0.000    -.2153174     -.17162
  log_asset_w |    .246793   .0033983    72.62   0.000     .2401318    .2534541
          coi |   .0227908   .0178458     1.28   0.202    -.0121894    .0577709
      whistle |   .1187888   .0133842     8.88   0.000     .0925539    .1450236
   audit_cmte |  -.0087248    .013029    -0.67   0.503    -.0342634    .0168138
        _cons |   4.944507   .0222127   222.60   0.000     4.900967    4.988047
-------------------------------------------------------------------------------

Absorbed degrees of freedom:
----------------------------------------------------------+
      Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------+---------------------------------------|
   ntee1_r#fyear2 |       275           0         275     |
----------------------------------------------------------+

. outreg2 using Output\T10B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Industry-Year FE, Y)
Output\T10B.xls
dir : seeout

. reghdfe log_tdc1_w char50contemp log_asset_w coi whistle audit_cmte log_rev_w debtat_w bd_ind_w family, abs(ntee1_r#fyear2) cluster(ein)
(dropped 2 singleton observations)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =     85,993
Absorbing 1 HDFE group                            F(   9,  14098) =     911.99
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5539
                                                  Adj R-squared   =     0.5525
                                                  Within R-sq.    =     0.3891
Number of clusters (ein)     =     14,099         Root MSE        =     0.4800

                                (Std. err. adjusted for 14,099 clusters in ein)
-------------------------------------------------------------------------------
              |               Robust
   log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
char50contemp |  -.0964889   .0107828    -8.95   0.000    -.1176246   -.0753531
  log_asset_w |   .1199416   .0052803    22.71   0.000     .1095914    .1302918
          coi |   .0085782   .0175708     0.49   0.625    -.0258629    .0430194
      whistle |   .1037321   .0129295     8.02   0.000     .0783885    .1290757
   audit_cmte |   .0042214   .0126866     0.33   0.739     -.020646    .0290888
    log_rev_w |   .1525996   .0055626    27.43   0.000     .1416962     .163503
     debtat_w |   .1385846   .0148333     9.34   0.000     .1095093    .1676599
     bd_ind_w |   -.331193   .0208747   -15.87   0.000    -.3721102   -.2902757
       family |   .0830611   .0090438     9.18   0.000      .065334    .1007881
        _cons |   5.149382   .0276394   186.31   0.000     5.095205    5.203559
-------------------------------------------------------------------------------

Absorbed degrees of freedom:
----------------------------------------------------------+
      Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------+---------------------------------------|
   ntee1_r#fyear2 |       275           0         275     |
----------------------------------------------------------+

. outreg2 using Output\T10B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Industry-Year FE, Y)
Output\T10B.xls
dir : seeout

. reghdfe log_tdc1_w femaleceo, abs(ntee1_r#fyear2) cluster(ein)
(dropped 2 singleton observations)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =     48,122
Absorbing 1 HDFE group                            F(   1,   8804) =      80.75
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2452
                                                  Adj R-squared   =     0.2413
                                                  Within R-sq.    =     0.0079
Number of clusters (ein)     =      8,805         Root MSE        =     0.6022

                                (Std. err. adjusted for 8,805 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   femaleceo |  -.1272285   .0141583    -8.99   0.000     -.154982    -.099475
       _cons |   6.146956   .0075482   814.36   0.000     6.132159    6.161752
------------------------------------------------------------------------------

Absorbed degrees of freedom:
----------------------------------------------------------+
      Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------+---------------------------------------|
   ntee1_r#fyear2 |       249           0         249     |
----------------------------------------------------------+

. outreg2 using Output\T10B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Industry-Year FE, Y)
Output\T10B.xls
dir : seeout

. reghdfe log_tdc1_w femaleceo log_asset_w coi whistle audit_cmte, abs(ntee1_r#fyear2) cluster(ein)
(dropped 2 singleton observations)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =     48,122
Absorbing 1 HDFE group                            F(   5,   8804) =     889.61
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4992
                                                  Adj R-squared   =     0.4965
                                                  Within R-sq.    =     0.3418
Number of clusters (ein)     =      8,805         Root MSE        =     0.4906

                                (Std. err. adjusted for 8,805 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   femaleceo |  -.0860559   .0110548    -7.78   0.000     -.107726   -.0643859
 log_asset_w |   .2623087   .0041558    63.12   0.000     .2541623    .2704551
         coi |  -.0441287   .0358609    -1.23   0.219    -.1144245     .026167
     whistle |   .0971368   .0196372     4.95   0.000     .0586433    .1356303
  audit_cmte |  -.0213105   .0214645    -0.99   0.321    -.0633859    .0207649
       _cons |    4.93665   .0394928   125.00   0.000     4.859234    5.014065
------------------------------------------------------------------------------

Absorbed degrees of freedom:
----------------------------------------------------------+
      Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------+---------------------------------------|
   ntee1_r#fyear2 |       249           0         249     |
----------------------------------------------------------+

. outreg2 using Output\T10B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Industry-Year FE, Y)
Output\T10B.xls
dir : seeout

. reghdfe log_tdc1_w femaleceo log_asset_w coi whistle audit_cmte log_rev_w debtat_w bd_ind_w family, abs(ntee1_r#fyear2) cluster(ein)
(dropped 2 singleton observations)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =     48,071
Absorbing 1 HDFE group                            F(   9,   8802) =     689.24
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5574
                                                  Adj R-squared   =     0.5550
                                                  Within R-sq.    =     0.4184
Number of clusters (ein)     =      8,803         Root MSE        =     0.4611

                                (Std. err. adjusted for 8,803 clusters in ein)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   femaleceo |  -.0637406   .0101967    -6.25   0.000    -.0837286   -.0437527
 log_asset_w |   .1206931   .0067969    17.76   0.000     .1073696    .1340167
         coi |  -.0160431   .0357643    -0.45   0.654    -.0861496    .0540633
     whistle |   .0828531   .0187196     4.43   0.000     .0461582    .1195479
  audit_cmte |  -.0058687   .0202599    -0.29   0.772    -.0455829    .0338454
   log_rev_w |   .1716077   .0072235    23.76   0.000     .1574479    .1857675
    debtat_w |   .1310421   .0193143     6.78   0.000     .0931815    .1689027
    bd_ind_w |  -.3330419   .0329266   -10.11   0.000    -.3975857   -.2684981
      family |   .0675106   .0105496     6.40   0.000      .046831    .0881902
       _cons |   5.112009   .0435091   117.49   0.000     5.026721    5.197297
------------------------------------------------------------------------------

Absorbed degrees of freedom:
----------------------------------------------------------+
      Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------+---------------------------------------|
   ntee1_r#fyear2 |       249           0         249     |
----------------------------------------------------------+

. outreg2 using Output\T10B.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Industry-Year FE, Y)
Output\T10B.xls
dir : seeout

. 
. *T11
. use amazon_apr22, clear

. 
. *number of unique organizations in the dataset
. distinct ein

----------------------------
     |     total   distinct
-----+----------------------
 ein |    405137      10695
----------------------------

. 
. set more off

. reghdfe log_tdc1_w gov_law10 if ceo==1, abs(ein fyear2) cluster(state)
(dropped 915 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     67,243
Absorbing 2 HDFE groups                           F(   1,     62) =      20.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8588
                                                  Adj R-squared   =     0.8349
                                                  Within R-sq.    =     0.0002
Number of clusters (state)   =         63         Root MSE        =     0.2501

                                 (Std. err. adjusted for 63 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0217805   .0048579    -4.48   0.000    -.0314913   -.0120698
       _cons |   12.83761   .0002353  5.5e+04   0.000     12.83714    12.83808
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      9732           0        9732     |
      fyear2 |         9           1           8     |
-----------------------------------------------------+

. outreg2 using Output\T11.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N) repl
> ace    
Output\T11.xls
dir : seeout

. reghdfe log_tdc1_w gov_law10 log_asset_w coi whistle audit_cmte if ceo==1, abs(ein fyear2) cluster(state)
(dropped 918 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     67,136
Absorbing 2 HDFE groups                           F(   5,     62) =      41.35
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8600
                                                  Adj R-squared   =     0.8363
                                                  Within R-sq.    =     0.0074
Number of clusters (state)   =         63         Root MSE        =     0.2491

                                 (Std. err. adjusted for 63 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0223289   .0043989    -5.08   0.000    -.0311222   -.0135355
 log_asset_w |   .0944683   .0079121    11.94   0.000     .0786523    .1102843
         coi |   .0068364   .0187207     0.37   0.716    -.0305857    .0442585
     whistle |   .0017944    .011276     0.16   0.874    -.0207459    .0243347
  audit_cmte |   .0157832   .0109992     1.43   0.156    -.0062039    .0377702
       _cons |   11.10756   .1415162    78.49   0.000     10.82468    11.39045
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      9719           0        9719     |
      fyear2 |         9           1           8     |
-----------------------------------------------------+

. outreg2 using Output\T11.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N)
Output\T11.xls
dir : seeout

. reghdfe log_tdc1_w gov_law10 log_asset_w coi whistle audit_cmte log_rev_w debt_asset_w bd_ind_w family if ceo==1, abs(ein fyear2) cluster(state)
(dropped 919 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     67,094
Absorbing 2 HDFE groups                           F(   9,     62) =      35.99
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8604
                                                  Adj R-squared   =     0.8367
                                                  Within R-sq.    =     0.0098
Number of clusters (state)   =         63         Root MSE        =     0.2487

                                 (Std. err. adjusted for 63 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0231129   .0041114    -5.62   0.000    -.0313315   -.0148944
 log_asset_w |   .0701469   .0083199     8.43   0.000     .0535157    .0867782
         coi |   .0046563   .0190825     0.24   0.808    -.0334892    .0428018
     whistle |   .0032094   .0114123     0.28   0.779    -.0196034    .0260223
  audit_cmte |   .0148093   .0108285     1.37   0.176    -.0068366    .0364552
   log_rev_w |   .0540084   .0084412     6.40   0.000     .0371347    .0708822
debt_asset_w |  -.0233498    .017422    -1.34   0.185    -.0581759    .0114764
    bd_ind_w |   .0054922   .0161483     0.34   0.735    -.0267877    .0377722
      family |   .0082926   .0067018     1.24   0.221    -.0051042    .0216894
       _cons |   10.60397   .1618299    65.53   0.000     10.28047    10.92746
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      9714           0        9714     |
      fyear2 |         9           1           8     |
-----------------------------------------------------+

. outreg2 using Output\T11.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N)
Output\T11.xls
dir : seeout

. reghdfe log_tdc1_w gov_law_ceo, abs(firm_yr firm_ceo year_ceo) cluster(state)
(dropped 14075 singleton observations)
(MWFE estimator converged in 11 iterations)

HDFE Linear regression                            Number of obs   =    391,062
Absorbing 3 HDFE groups                           F(   1,     64) =      13.38
Statistics robust to heteroskedasticity           Prob > F        =     0.0005
                                                  R-squared       =     0.7606
                                                  Adj R-squared   =     0.7108
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         65         Root MSE        =     0.3030

                                 (Std. err. adjusted for 65 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |  -.0183635   .0050195    -3.66   0.001     -.028391    -.008336
       _cons |   12.62938   .0000339  3.7e+05   0.000     12.62931    12.62945
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     50733       50733           0    *|
    firm_ceo |     16645           0       16645     |
    year_ceo |        19           2          17     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T11.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y, CEO-Ind-Year FE, N)
Output\T11.xls
dir : seeout

. reghdfe log_tdc1_w gov_law_ceo if (state=="PA" | state=="NJ" | state=="CT" | state=="MA" | state=="VT" | state=="NY") , a(firm_yr firm_ceo year_ceo) cluster(state)
(dropped 2797 singleton observations)
(MWFE estimator converged in 9 iterations)

HDFE Linear regression                            Number of obs   =    108,290
Absorbing 3 HDFE groups                           F(   1,      5) =      13.19
Statistics robust to heteroskedasticity           Prob > F        =     0.0150
                                                  R-squared       =     0.7778
                                                  Adj R-squared   =     0.7345
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =          6         Root MSE        =     0.2828

                                  (Std. err. adjusted for 6 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |  -.0222726   .0061333    -3.63   0.015    -.0380386   -.0065065
       _cons |   12.62531   .0001494  8.5e+04   0.000     12.62492    12.62569
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     13398       13398           0    *|
    firm_ceo |      4236           0        4236     |
    year_ceo |        19           2          17     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T11.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y, CEO-Ind-Year FE, N)
Output\T11.xls
dir : seeout

. reghdfe log_tdc1_w gov_law_ceo, abs(firm_yr firm_ceo ceo_yr_ind) cluster(state)
(dropped 14075 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =    391,062
Absorbing 3 HDFE groups                           F(   1,     64) =      29.51
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7608
                                                  Adj R-squared   =     0.7106
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         65         Root MSE        =     0.3031

                                 (Std. err. adjusted for 65 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |  -.0254676   .0046885    -5.43   0.000    -.0348339   -.0161013
       _cons |   12.62943   .0000316  4.0e+05   0.000     12.62937    12.62949
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     50733       50733           0    *|
    firm_ceo |     16645           0       16645     |
  ceo_yr_ind |       452          51         401     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\T11.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, N, CEO-Ind-Year FE, Y)
Output\T11.xls
dir : seeout

. 
. *T12
. use amazon_apr22, clear

. set more off

. reghdfe log_tdc1_w gov_law10 if ceo==1, abs(ein_name_title fyear2) cluster(state)
(dropped 10975 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     57,123
Absorbing 2 HDFE groups                           F(   1,     61) =      33.42
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9453
                                                  Adj R-squared   =     0.9273
                                                  Within R-sq.    =     0.0003
Number of clusters (state)   =         62         Root MSE        =     0.1637

                                 (Std. err. adjusted for 62 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0209641   .0036266    -5.78   0.000    -.0282159   -.0137122
       _cons |   12.83505   .0001672  7.7e+04   0.000     12.83472    12.83539
------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------+
    Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------+---------------------------------------|
 ein_name_title |     14098           0       14098     |
         fyear2 |         9           1           8     |
--------------------------------------------------------+

. outreg2 using Output\T12.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, Y, Firm-Person-Title FE, Y) replace     
Output\T12.xls
dir : seeout

. reghdfe log_tdc1_w gov_law10 log_asset_w coi whistle audit_cmte if ceo==1, abs(ein_name_title fyear2) cluster(state)
(dropped 10953 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     57,041
Absorbing 2 HDFE groups                           F(   5,     61) =      24.67
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9457
                                                  Adj R-squared   =     0.9279
                                                  Within R-sq.    =     0.0058
Number of clusters (state)   =         62         Root MSE        =     0.1630

                                 (Std. err. adjusted for 62 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0217689   .0033323    -6.53   0.000    -.0284322   -.0151056
 log_asset_w |    .063419   .0089258     7.11   0.000     .0455707    .0812673
         coi |  -.0150177   .0329792    -0.46   0.650    -.0809637    .0509282
     whistle |  -.0065694   .0071326    -0.92   0.361     -.020832    .0076932
  audit_cmte |   .0219727   .0096629     2.27   0.027     .0026506    .0412948
       _cons |   11.69184    .152263    76.79   0.000     11.38737    11.99631
------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------+
    Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------+---------------------------------------|
 ein_name_title |     14079           0       14079     |
         fyear2 |         9           1           8     |
--------------------------------------------------------+

. outreg2 using Output\T12.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, Y, Firm-Person-Title FE, Y)
Output\T12.xls
dir : seeout

. reghdfe log_tdc1_w gov_law10 log_asset_w coi whistle audit_cmte log_rev_w debt_asset_w bd_ind_w family if ceo==1, abs(ein_name_title fyear2) cluster(state)
(dropped 10948 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     57,005
Absorbing 2 HDFE groups                           F(   9,     61) =      22.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9459
                                                  Adj R-squared   =     0.9282
                                                  Within R-sq.    =     0.0089
Number of clusters (state)   =         62         Root MSE        =     0.1627

                                 (Std. err. adjusted for 62 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   -.022559   .0030945    -7.29   0.000    -.0287468   -.0163711
 log_asset_w |   .0439041   .0090897     4.83   0.000     .0257282      .06208
         coi |  -.0158154   .0327789    -0.48   0.631     -.081361    .0497301
     whistle |  -.0054917   .0072745    -0.75   0.453    -.0200379    .0090546
  audit_cmte |   .0214624   .0093622     2.29   0.025     .0027414    .0401833
   log_rev_w |   .0452639   .0055742     8.12   0.000     .0341175    .0564102
debt_asset_w |  -.0157421    .017415    -0.90   0.370    -.0505654    .0190813
    bd_ind_w |   -.009298   .0176511    -0.53   0.600    -.0445935    .0259975
      family |    .004392   .0051676     0.85   0.399    -.0059413    .0147254
       _cons |   11.26621   .1795984    62.73   0.000     10.90708    11.62534
------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------+
    Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------+---------------------------------------|
 ein_name_title |     14072           0       14072     |
         fyear2 |         9           1           8     |
--------------------------------------------------------+

. outreg2 using Output\T12.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, Y, Firm-Person-Title FE, Y)
Output\T12.xls
dir : seeout

. reghdfe turn2 gov_law10 if ceo==1, abs(ein fyear2) cluster(state)
(dropped 748 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     55,887
Absorbing 2 HDFE groups                           F(   1,     60) =       0.68
Statistics robust to heteroskedasticity           Prob > F        =     0.4135
                                                  R-squared       =     0.2455
                                                  Adj R-squared   =     0.1020
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         61         Root MSE        =     0.3357

                                 (Std. err. adjusted for 61 clusters in state)
------------------------------------------------------------------------------
             |               Robust
       turn2 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0034588   .0042001     0.82   0.413    -.0049426    .0118601
       _cons |   .1470154   .0002345   626.97   0.000     .1465464    .1474844
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      8924           0        8924     |
      fyear2 |         8           1           7     |
-----------------------------------------------------+

. outreg2 using Output\T12.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Person-Title FE, N)
Output\T12.xls
dir : seeout

. reghdfe turn2 gov_law10 log_asset_w coi whistle audit_cmte if ceo==1, abs(ein fyear2) cluster(state)
(dropped 756 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     55,791
Absorbing 2 HDFE groups                           F(   5,     60) =       1.38
Statistics robust to heteroskedasticity           Prob > F        =     0.2454
                                                  R-squared       =     0.2461
                                                  Adj R-squared   =     0.1027
                                                  Within R-sq.    =     0.0003
Number of clusters (state)   =         61         Root MSE        =     0.3356

                                 (Std. err. adjusted for 61 clusters in state)
------------------------------------------------------------------------------
             |               Robust
       turn2 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0034436   .0041975     0.82   0.415    -.0049527    .0118398
 log_asset_w |  -.0259603   .0113785    -2.28   0.026    -.0487207   -.0031999
         coi |   .0160652   .0306135     0.52   0.602    -.0451708    .0773012
     whistle |  -.0135791   .0193485    -0.70   0.486    -.0522818    .0251236
  audit_cmte |  -.0015173   .0193015    -0.08   0.938    -.0401259    .0370914
       _cons |   .6159826   .2034978     3.03   0.004     .2089265    1.023039
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      8904           0        8904     |
      fyear2 |         8           1           7     |
-----------------------------------------------------+

. outreg2 using Output\T12.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Person-Title FE, N)
Output\T12.xls
dir : seeout

. reghdfe turn2 gov_law10 log_asset_w coi whistle audit_cmte log_rev_w debt_asset_w bd_ind_w family if ceo==1, abs(ein fyear2) cluster(state)
(dropped 758 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     55,764
Absorbing 2 HDFE groups                           F(   9,     60) =       4.12
Statistics robust to heteroskedasticity           Prob > F        =     0.0004
                                                  R-squared       =     0.2465
                                                  Adj R-squared   =     0.1031
                                                  Within R-sq.    =     0.0007
Number of clusters (state)   =         61         Root MSE        =     0.3356

                                 (Std. err. adjusted for 61 clusters in state)
------------------------------------------------------------------------------
             |               Robust
       turn2 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0035696   .0041962     0.85   0.398    -.0048241    .0119632
 log_asset_w |  -.0161842   .0129105    -1.25   0.215    -.0420091    .0096407
         coi |   .0162686   .0306025     0.53   0.597    -.0449456    .0774828
     whistle |  -.0141331   .0193309    -0.73   0.468    -.0528006    .0245344
  audit_cmte |   -.001021   .0191008    -0.05   0.958    -.0392282    .0371862
   log_rev_w |  -.0198582   .0094326    -2.11   0.039    -.0387261   -.0009902
debt_asset_w |   .0523624   .0192788     2.72   0.009     .0137991    .0909257
    bd_ind_w |  -.0385546   .0293697    -1.31   0.194    -.0973027    .0201935
      family |  -.0046148   .0104808    -0.44   0.661    -.0255795    .0163498
       _cons |   .8029262   .2173429     3.69   0.000     .3681756    1.237677
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      8901           0        8901     |
      fyear2 |         8           1           7     |
-----------------------------------------------------+

. outreg2 using Output\T12.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Person-Title FE, N)
Output\T12.xls
dir : seeout

. 
. *C1
. use ceo_apr22, clear

. * use only qtile columns (3,6,9,12,15,18)
. set more off

. mmqreg log_tdc1_w gov_law10 if sample==1, abs(ein fyear2) cluster(state_r) q(25)
WARNING: some fitted values of the scale function are negative
Consider using a different model specification
395 Observations have negative predicted Scale values
MM-qreg Estimator
Number of obs = 84421
Quantile:  25
                               (Std. err. adjusted for 53 clusters in state_r)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
location     |
   gov_law10 |  -.0167575   .0033323    -5.03   0.000    -.0232887   -.0102264
       _cons |   6.036999   .0002075  2.9e+04   0.000     6.036592    6.037405
-------------+----------------------------------------------------------------
scale        |
   gov_law10 |    .003821   .0010305     3.71   0.000     .0018014    .0058407
       _cons |   .1221056   .0000575  2123.86   0.000     .1219929    .1222183
-------------+----------------------------------------------------------------
qtile        |
   gov_law10 |  -.0201547   .0036067    -5.59   0.000    -.0272237   -.0130856
       _cons |   5.928439   .0006799  8719.00   0.000     5.927106    5.929771
------------------------------------------------------------------------------

. outreg2 using Output\C1.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) replace     
Output\C1.xls
dir : seeout

. mmqreg log_tdc1_w gov_law10 log_asset_w coi whistle audit_cmte log_rev_w debtat_w bd_ind_w family if sample==1, abs(ein fyear2) cluster(state_r) q(25)
WARNING: some fitted values of the scale function are negative
Consider using a different model specification
317 Observations have negative predicted Scale values
MM-qreg Estimator
Number of obs = 84225
Quantile:  25
                               (Std. err. adjusted for 53 clusters in state_r)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
location     |
   gov_law10 |  -.0161273   .0031677    -5.09   0.000    -.0223359   -.0099187
 log_asset_w |   .0702645   .0082306     8.54   0.000     .0541328    .0863961
         coi |   .0021939    .011587     0.19   0.850    -.0205163     .024904
     whistle |  -.0111404   .0057551    -1.94   0.053    -.0224201    .0001394
  audit_cmte |   .0148744   .0064181     2.32   0.020     .0022952    .0274536
   log_rev_w |   .0391037   .0049675     7.87   0.000     .0293675    .0488399
    debtat_w |   .0264394   .0102914     2.57   0.010     .0062686    .0466102
    bd_ind_w |  -.0825614   .0199391    -4.14   0.000    -.1216413   -.0434816
      family |   .0138926   .0060638     2.29   0.022     .0020079    .0257774
       _cons |   5.662321   .0400742   141.30   0.000     5.583777    5.740865
-------------+----------------------------------------------------------------
scale        |
   gov_law10 |   .0028996   .0010669     2.72   0.007     .0008086    .0049907
 log_asset_w |  -.0053171   .0030705    -1.73   0.083    -.0113353    .0007011
         coi |   .0038706   .0042029     0.92   0.357    -.0043668    .0121081
     whistle |  -.0045182   .0040381    -1.12   0.263    -.0124326    .0033963
  audit_cmte |  -.0115668   .0027293    -4.24   0.000    -.0169162   -.0062175
   log_rev_w |   -.007017   .0029385    -2.39   0.017    -.0127764   -.0012576
    debtat_w |   .0020058   .0056886     0.35   0.724    -.0091437    .0131553
    bd_ind_w |   .0017136   .0054998     0.31   0.755    -.0090659    .0124931
      family |  -.0001335   .0021611    -0.06   0.951    -.0043691    .0041021
       _cons |   .1768755   .0123311    14.34   0.000      .152707     .201044
-------------+----------------------------------------------------------------
qtile        |
   gov_law10 |  -.0187061   .0034097    -5.49   0.000    -.0253891   -.0120232
 log_asset_w |   .0749933   .0087622     8.56   0.000     .0578196     .092167
         coi |  -.0012485   .0133583    -0.09   0.926    -.0274303    .0249333
     whistle |  -.0071221   .0069309    -1.03   0.304    -.0207065    .0064623
  audit_cmte |   .0251615   .0073197     3.44   0.001     .0108152    .0395078
   log_rev_w |   .0453444   .0052947     8.56   0.000     .0349669    .0557218
    debtat_w |   .0246556   .0125284     1.97   0.049     .0001003    .0492108
    bd_ind_w |  -.0840854   .0200876    -4.19   0.000    -.1234563   -.0447145
      family |   .0140113   .0061831     2.27   0.023     .0018927    .0261299
       _cons |   5.505015   .0411884   133.65   0.000     5.424288    5.585743
------------------------------------------------------------------------------

. outreg2 using Output\C1.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)
Output\C1.xls
dir : seeout

. mmqreg log_tdc1_w gov_law10 if sample==1, abs(ein fyear2) cluster(state_r) q(50)
WARNING: some fitted values of the scale function are negative
Consider using a different model specification
395 Observations have negative predicted Scale values
MM-qreg Estimator
Number of obs = 84421
Quantile:  50
                               (Std. err. adjusted for 53 clusters in state_r)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
location     |
   gov_law10 |  -.0167575   .0033323    -5.03   0.000    -.0232887   -.0102264
       _cons |   6.036999   .0002075  2.9e+04   0.000     6.036592    6.037405
-------------+----------------------------------------------------------------
scale        |
   gov_law10 |    .003821   .0010305     3.71   0.000     .0018014    .0058407
       _cons |   .1221056   .0000575  2123.86   0.000     .1219929    .1222183
-------------+----------------------------------------------------------------
qtile        |
   gov_law10 |  -.0167818   .0033401    -5.02   0.000    -.0233282   -.0102354
       _cons |   6.036224   .0011378  5305.30   0.000     6.033994    6.038454
------------------------------------------------------------------------------

. outreg2 using Output\C1.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)
Output\C1.xls
dir : seeout

. mmqreg log_tdc1_w gov_law10 log_asset_w coi whistle audit_cmte log_rev_w debtat_w bd_ind_w family if sample==1, abs(ein fyear2) cluster(state_r) q(50)
WARNING: some fitted values of the scale function are negative
Consider using a different model specification
317 Observations have negative predicted Scale values
MM-qreg Estimator
Number of obs = 84225
Quantile:  50
                               (Std. err. adjusted for 53 clusters in state_r)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
location     |
   gov_law10 |  -.0161273   .0031677    -5.09   0.000    -.0223359   -.0099187
 log_asset_w |   .0702645   .0082306     8.54   0.000     .0541328    .0863961
         coi |   .0021939    .011587     0.19   0.850    -.0205163     .024904
     whistle |  -.0111404   .0057551    -1.94   0.053    -.0224201    .0001394
  audit_cmte |   .0148744   .0064181     2.32   0.020     .0022952    .0274536
   log_rev_w |   .0391037   .0049675     7.87   0.000     .0293675    .0488399
    debtat_w |   .0264394   .0102914     2.57   0.010     .0062686    .0466102
    bd_ind_w |  -.0825614   .0199391    -4.14   0.000    -.1216413   -.0434816
      family |   .0138926   .0060638     2.29   0.022     .0020079    .0257774
       _cons |   5.662321   .0400742   141.30   0.000     5.583777    5.740865
-------------+----------------------------------------------------------------
scale        |
   gov_law10 |   .0028996   .0010669     2.72   0.007     .0008086    .0049907
 log_asset_w |  -.0053171   .0030705    -1.73   0.083    -.0113353    .0007011
         coi |   .0038706   .0042029     0.92   0.357    -.0043668    .0121081
     whistle |  -.0045182   .0040381    -1.12   0.263    -.0124326    .0033963
  audit_cmte |  -.0115668   .0027293    -4.24   0.000    -.0169162   -.0062175
   log_rev_w |   -.007017   .0029385    -2.39   0.017    -.0127764   -.0012576
    debtat_w |   .0020058   .0056886     0.35   0.724    -.0091437    .0131553
    bd_ind_w |   .0017136   .0054998     0.31   0.755    -.0090659    .0124931
      family |  -.0001335   .0021611    -0.06   0.951    -.0043691    .0041021
       _cons |   .1768755   .0123311    14.34   0.000      .152707     .201044
-------------+----------------------------------------------------------------
qtile        |
   gov_law10 |  -.0161542   .0031753    -5.09   0.000    -.0223777   -.0099307
 log_asset_w |   .0703138   .0082543     8.52   0.000     .0541356     .086492
         coi |    .002158   .0116051     0.19   0.852    -.0205875    .0249034
     whistle |  -.0110985   .0057526    -1.93   0.054    -.0223734    .0001765
  audit_cmte |   .0149817    .006415     2.34   0.020     .0024086    .0275548
   log_rev_w |   .0391688   .0049732     7.88   0.000     .0294214    .0489161
    debtat_w |   .0264208   .0103088     2.56   0.010      .006216    .0466256
    bd_ind_w |  -.0825773    .019935    -4.14   0.000    -.1216492   -.0435055
      family |   .0138939   .0060613     2.29   0.022      .002014    .0257737
       _cons |   5.660681   .0406592   139.22   0.000      5.58099    5.740372
------------------------------------------------------------------------------

. outreg2 using Output\C1.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)
Output\C1.xls
dir : seeout

. mmqreg log_tdc1_w gov_law10 if sample==1, abs(ein fyear2) cluster(state_r) q(75)
WARNING: some fitted values of the scale function are negative
Consider using a different model specification
395 Observations have negative predicted Scale values
MM-qreg Estimator
Number of obs = 84421
Quantile:  75
                               (Std. err. adjusted for 53 clusters in state_r)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
location     |
   gov_law10 |  -.0167575   .0033323    -5.03   0.000    -.0232887   -.0102264
       _cons |   6.036999   .0002075  2.9e+04   0.000     6.036592    6.037405
-------------+----------------------------------------------------------------
scale        |
   gov_law10 |    .003821   .0010305     3.71   0.000     .0018014    .0058407
       _cons |   .1221056   .0000575  2123.86   0.000     .1219929    .1222183
-------------+----------------------------------------------------------------
qtile        |
   gov_law10 |  -.0133778   .0032945    -4.06   0.000    -.0198349   -.0069207
       _cons |   6.145001    .000741  8292.57   0.000     6.143549    6.146454
------------------------------------------------------------------------------

. outreg2 using Output\C1.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)
Output\C1.xls
dir : seeout

. mmqreg log_tdc1_w gov_law10 log_asset_w coi whistle audit_cmte log_rev_w debtat_w bd_ind_w family if sample==1, abs(ein fyear2) cluster(state_r) q(75)
WARNING: some fitted values of the scale function are negative
Consider using a different model specification
317 Observations have negative predicted Scale values
MM-qreg Estimator
Number of obs = 84225
Quantile:  75
                               (Std. err. adjusted for 53 clusters in state_r)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
location     |
   gov_law10 |  -.0161273   .0031677    -5.09   0.000    -.0223359   -.0099187
 log_asset_w |   .0702645   .0082306     8.54   0.000     .0541328    .0863961
         coi |   .0021939    .011587     0.19   0.850    -.0205163     .024904
     whistle |  -.0111404   .0057551    -1.94   0.053    -.0224201    .0001394
  audit_cmte |   .0148744   .0064181     2.32   0.020     .0022952    .0274536
   log_rev_w |   .0391037   .0049675     7.87   0.000     .0293675    .0488399
    debtat_w |   .0264394   .0102914     2.57   0.010     .0062686    .0466102
    bd_ind_w |  -.0825614   .0199391    -4.14   0.000    -.1216413   -.0434816
      family |   .0138926   .0060638     2.29   0.022     .0020079    .0257774
       _cons |   5.662321   .0400742   141.30   0.000     5.583777    5.740865
-------------+----------------------------------------------------------------
scale        |
   gov_law10 |   .0028996   .0010669     2.72   0.007     .0008086    .0049907
 log_asset_w |  -.0053171   .0030705    -1.73   0.083    -.0113353    .0007011
         coi |   .0038706   .0042029     0.92   0.357    -.0043668    .0121081
     whistle |  -.0045182   .0040381    -1.12   0.263    -.0124326    .0033963
  audit_cmte |  -.0115668   .0027293    -4.24   0.000    -.0169162   -.0062175
   log_rev_w |   -.007017   .0029385    -2.39   0.017    -.0127764   -.0012576
    debtat_w |   .0020058   .0056886     0.35   0.724    -.0091437    .0131553
    bd_ind_w |   .0017136   .0054998     0.31   0.755    -.0090659    .0124931
      family |  -.0001335   .0021611    -0.06   0.951    -.0043691    .0041021
       _cons |   .1768755   .0123311    14.34   0.000      .152707     .201044
-------------+----------------------------------------------------------------
qtile        |
   gov_law10 |  -.0135628   .0031983    -4.24   0.000    -.0198314   -.0072943
 log_asset_w |    .065562   .0085918     7.63   0.000     .0487223    .0824016
         coi |   .0056171   .0108756     0.52   0.606    -.0156987    .0269329
     whistle |  -.0151363   .0066244    -2.28   0.022    -.0281198   -.0021527
  audit_cmte |   .0046446    .006368     0.73   0.466    -.0078365    .0171257
   log_rev_w |   .0328978   .0059101     5.57   0.000     .0213143    .0444813
    debtat_w |   .0282134   .0102895     2.74   0.006     .0080463    .0483804
    bd_ind_w |  -.0810459   .0209562    -3.87   0.000    -.1221194   -.0399724
      family |   .0137746   .0065301     2.11   0.035     .0009757    .0265734
       _cons |   5.818752   .0422276   137.80   0.000     5.735987    5.901516
------------------------------------------------------------------------------

. outreg2 using Output\C1.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)
Output\C1.xls
dir : seeout

. 
. *C2
. use ceo_apr22, clear

. set more off

. reghdfe log_tdc1_w gov_law10 if coi_whistle_audit==1, abs(ein fyear2) cluster(state)
(dropped 90 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     63,507
Absorbing 2 HDFE groups                           F(   1,     52) =      22.79
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9272
                                                  Adj R-squared   =     0.9166
                                                  Within R-sq.    =     0.0002
Number of clusters (state)   =         53         Root MSE        =     0.2073

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0166223    .003482    -4.77   0.000    -.0236095   -.0096351
       _cons |   6.134125   .0002069  3.0e+04   0.000      6.13371     6.13454
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      8072           0        8072     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C2.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N) repla
> ce     
Output\C2.xls
dir : seeout

. 
. use both_apr22, clear

. set more off

. reghdfe log_tdc1_w gov_law_ceo if coi_whistle_audit==1, abs(firm_yr firm_ceo year_ceo) cluster(state)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =    387,816
Absorbing 3 HDFE groups                           F(   1,     52) =      32.24
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8017
                                                  Adj R-squared   =     0.7645
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.3021

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |   -.017044   .0030016    -5.68   0.000    -.0230671   -.0110209
       _cons |   5.802495   .0000189  3.1e+05   0.000     5.802457    5.802533
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     47313       47313           0    *|
    firm_ceo |     13969           0       13969     |
    year_ceo |        22           2          20     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\C2.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y, CEO-Ind-Year FE, N)
Output\C2.xls
dir : seeout

. 
. use ceo_apr22, clear

. set more off

. reghdfe avg_hrs_per_wk_w gov_law10 if coi_whistle_audit==1, abs(ein fyear2) cluster(state)
(dropped 817 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     31,814
Absorbing 2 HDFE groups                           F(   1,     52) =      63.00
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8335
                                                  Adj R-squared   =     0.7965
                                                  Within R-sq.    =     0.0005
Number of clusters (state)   =         53         Root MSE        =     3.7231

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |    .611142   .0769936     7.94   0.000     .4566429     .765641
       _cons |   45.55911   .0046022  9899.47   0.000     45.54987    45.56834
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      5779           0        5779     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C2.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N) 
Output\C2.xls
dir : seeout

. 
. use both_apr22, clear

. set more off

. reghdfe avg_hrs_per_wk_w gov_law_ceo if coi_whistle_audit==1, abs(firm_yr firm_ceo year_ceo) cluster(state)
(dropped 1202 singleton observations)
(MWFE estimator converged in 10 iterations)

HDFE Linear regression                            Number of obs   =    152,141
Absorbing 3 HDFE groups                           F(   1,     52) =      35.92
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7161
                                                  Adj R-squared   =     0.6531
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     4.5056

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |    .552271   .0921524     5.99   0.000     .3673537    .7371884
       _cons |   45.35761   .0004827  9.4e+04   0.000     45.35664    45.35858
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     18799       18799           0    *|
    firm_ceo |      8828           0        8828     |
    year_ceo |        22           2          20     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\C2.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y, CEO-Ind-Year FE, N)
Output\C2.xls
dir : seeout

. 
. use ceo_apr22, clear

. set more off

. reghdfe log_tdc1_w gov_law10 if eo38drops==0, abs(ein fyear2) cluster(state)
(dropped 1810 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     82,098
Absorbing 2 HDFE groups                           F(   1,     52) =      39.90
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9314
                                                  Adj R-squared   =     0.9193
                                                  Within R-sq.    =     0.0003
Number of clusters (state)   =         53         Root MSE        =     0.2033

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |  -.0240457   .0038065    -6.32   0.000    -.0316841   -.0164073
       _cons |   6.030498   .0002006  3.0e+04   0.000     6.030096    6.030901
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12286           0       12286     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C2.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N)     
Output\C2.xls
dir : seeout

. 
. use both_apr22, clear

. set more off

. reghdfe log_tdc1_w gov_law_ceo if eo38drops==0, abs(firm_yr firm_ceo year_ceo) cluster(state)
(dropped 75 singleton observations)
(MWFE estimator converged in 9 iterations)

HDFE Linear regression                            Number of obs   =    431,554
Absorbing 3 HDFE groups                           F(   1,     52) =      62.76
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8003
                                                  Adj R-squared   =     0.7596
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.3001

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
  log_tdc1_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |  -.0271371   .0034255    -7.92   0.000    -.0340109   -.0202634
       _cons |   5.775141   .0000166  3.5e+05   0.000     5.775108    5.775175
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     55081       55081           0    *|
    firm_ceo |     18065           0       18065     |
    year_ceo |        22           2          20     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\C2.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y, CEO-Ind-Year FE, N)
Output\C2.xls
dir : seeout

. 
. use ceo_apr22, clear

. set more off

. reghdfe avg_hrs_per_wk_w gov_law10 if eo38drops==0, abs(ein fyear2) cluster(state)
(dropped 2452 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     43,921
Absorbing 2 HDFE groups                           F(   1,     52) =       8.88
Statistics robust to heteroskedasticity           Prob > F        =     0.0044
                                                  R-squared       =     0.8369
                                                  Adj R-squared   =     0.7963
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     3.6342

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .2001613   .0671553     2.98   0.004     .0654044    .3349183
       _cons |   45.15361   .0036323  1.2e+04   0.000     45.14632     45.1609
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      8758           0        8758     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C2.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y, Firm-Year FE, N, Firm-CEO FE, N, CEO-Year FE, N, CEO-Ind-Year FE, N)     
Output\C2.xls
dir : seeout

. 
. use both_apr22, clear

. set more off

. reghdfe avg_hrs_per_wk_w gov_law_ceo if eo38drops==0, abs(firm_yr firm_ceo year_ceo) cluster(state)
(dropped 1589 singleton observations)
(MWFE estimator converged in 10 iterations)

HDFE Linear regression                            Number of obs   =    168,979
Absorbing 3 HDFE groups                           F(   1,     52) =      14.06
Statistics robust to heteroskedasticity           Prob > F        =     0.0004
                                                  R-squared       =     0.7149
                                                  Adj R-squared   =     0.6458
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     4.5358

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
avg_hrs_pe~w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
 gov_law_ceo |   .3501186   .0933735     3.75   0.000      .162751    .5374862
       _cons |   45.34958   .0003697  1.2e+05   0.000     45.34884    45.35032
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     firm_yr |     22075       22075           0    *|
    firm_ceo |     10837           0       10837     |
    year_ceo |        22           2          20     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using Output\C2.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, N, Year FE, N, Firm-Year FE, Y, Firm-CEO FE, Y, CEO-Year FE, Y, CEO-Ind-Year FE, N)
Output\C2.xls
dir : seeout

. 
. *C3
. use ceo_apr22, clear

. reghdfe rev_emp_w gov_law10, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,421
Absorbing 2 HDFE groups                           F(   1,     52) =      29.43
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8920
                                                  Adj R-squared   =     0.8736
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     0.2743

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
   rev_emp_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0202186   .0037272     5.42   0.000     .0127394    .0276978
       _cons |   .3262911   .0002014  1620.10   0.000     .3258869    .3266952
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12332           0       12332     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C3.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) replace
Output\C3.xls
dir : seeout

. reghdfe rev_emp_w gov_law10 log_asset_w coi whistle audit_cmte, abs(ein fyear2) cluster(state)
(dropped 1779 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,417
Absorbing 2 HDFE groups                           F(   5,     52) =      37.40
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8931
                                                  Adj R-squared   =     0.8748
                                                  Within R-sq.    =     0.0103
Number of clusters (state)   =         53         Root MSE        =     0.2729

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
   rev_emp_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0204667   .0034638     5.91   0.000     .0135161    .0274174
 log_asset_w |    .140505   .0139821    10.05   0.000     .1124479     .168562
         coi |  -.0184863   .0192637    -0.96   0.342    -.0571418    .0201693
     whistle |   -.002924   .0094849    -0.31   0.759    -.0219568    .0161088
  audit_cmte |  -.0069967   .0084837    -0.82   0.413    -.0240204     .010027
       _cons |  -.2322212   .0613485    -3.79   0.000     -.355326   -.1091163
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12331           0       12331     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C3.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)    
Output\C3.xls
dir : seeout

. reghdfe rev_emp_w gov_law10 if coi_whistle_audit==1, abs(ein fyear2) cluster(state)
(dropped 90 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     63,507
Absorbing 2 HDFE groups                           F(   1,     52) =      16.83
Statistics robust to heteroskedasticity           Prob > F        =     0.0001
                                                  R-squared       =     0.8844
                                                  Adj R-squared   =     0.8676
                                                  Within R-sq.    =     0.0001
Number of clusters (state)   =         53         Root MSE        =     0.2603

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
   rev_emp_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0182308   .0044438     4.10   0.000     .0093136     .027148
       _cons |   .3037951   .0002598  1169.34   0.000     .3032737    .3043164
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      8072           0        8072     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C3.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)    
Output\C3.xls
dir : seeout

. reghdfe program_w gov_law10, abs(ein fyear2) cluster(state)
(dropped 1464 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     65,929
Absorbing 2 HDFE groups                           F(   1,     52) =       4.81
Statistics robust to heteroskedasticity           Prob > F        =     0.0328
                                                  R-squared       =     0.8380
                                                  Adj R-squared   =     0.8100
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.0460

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
   program_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0019986   .0009112     2.19   0.033     .0001702    .0038271
       _cons |   .8292173   .0000528  1.6e+04   0.000     .8291114    .8293232
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      9697           0        9697     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C3.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)    
Output\C3.xls
dir : seeout

. reghdfe program_w gov_law10 log_asset_w coi whistle audit_cmte, abs(ein fyear2) cluster(state)
(dropped 1465 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     65,925
Absorbing 2 HDFE groups                           F(   5,     52) =       1.85
Statistics robust to heteroskedasticity           Prob > F        =     0.1195
                                                  R-squared       =     0.8381
                                                  Adj R-squared   =     0.8102
                                                  Within R-sq.    =     0.0011
Number of clusters (state)   =         53         Root MSE        =     0.0460

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
   program_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0019669   .0009038     2.18   0.034     .0001533    .0037806
 log_asset_w |    .007203   .0040903     1.76   0.084    -.0010048    .0154108
         coi |   .0019893   .0045828     0.43   0.666    -.0072067    .0111853
     whistle |   .0013286   .0025123     0.53   0.599    -.0037127      .00637
  audit_cmte |  -.0009381   .0022449    -0.42   0.678    -.0054429    .0035667
       _cons |   .7947521   .0205145    38.74   0.000     .7535867    .8359175
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      9696           0        9696     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C3.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)    
Output\C3.xls
dir : seeout

. reghdfe program_w gov_law10 if coi_whistle_audit==1, abs(ein fyear2) cluster(state)
(dropped 78 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     53,361
Absorbing 2 HDFE groups                           F(   1,     52) =       2.12
Statistics robust to heteroskedasticity           Prob > F        =     0.1512
                                                  R-squared       =     0.8408
                                                  Adj R-squared   =     0.8172
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.0433

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
   program_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0014647   .0010054     1.46   0.151    -.0005529    .0034822
       _cons |   .8315046   .0000603  1.4e+04   0.000     .8313837    .8316256
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      6857           0        6857     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C3.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)    
Output\C3.xls
dir : seeout

. 
. *C4
. use ceo_apr22, clear

. set more off

. reghdfe log_wage2_w gov_law10, abs(ein fyear2) cluster(state)
(dropped 1772 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,247
Absorbing 2 HDFE groups                           F(   1,     52) =       0.12
Statistics robust to heteroskedasticity           Prob > F        =     0.7288
                                                  R-squared       =     0.9482
                                                  Adj R-squared   =     0.9393
                                                  Within R-sq.    =     0.0000
Number of clusters (state)   =         53         Root MSE        =     0.1759

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
 log_wage2_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |   .0010492   .0030097     0.35   0.729    -.0049903    .0070886
       _cons |   3.876321   .0001509  2.6e+04   0.000     3.876019    3.876624
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12301           0       12301     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C4.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y) replace
Output\C4.xls
dir : seeout

. reghdfe log_wage2_w gov_law10 log_asset_w coi whistle audit_cmte, abs(ein fyear2) cluster(state)
(dropped 1772 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     84,243
Absorbing 2 HDFE groups                           F(   5,     52) =       7.94
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9482
                                                  Adj R-squared   =     0.9394
                                                  Within R-sq.    =     0.0015
Number of clusters (state)   =         53         Root MSE        =     0.1758

                                 (Std. err. adjusted for 53 clusters in state)
------------------------------------------------------------------------------
             |               Robust
 log_wage2_w | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   gov_law10 |    .001117   .0029287     0.38   0.704    -.0047599    .0069939
 log_asset_w |   .0339144   .0067427     5.03   0.000     .0203842    .0474447
         coi |  -.0075693   .0130278    -0.58   0.564    -.0337114    .0185728
     whistle |    .004134   .0093697     0.44   0.661    -.0146678    .0229357
  audit_cmte |   .0032714   .0051538     0.63   0.528    -.0070704    .0136132
       _cons |   3.735545   .0349787   106.79   0.000     3.665355    3.805735
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |     12300           0       12300     |
      fyear2 |        11           1          10     |
-----------------------------------------------------+

. outreg2 using Output\C4.xls, tstat bracket label excel bdec(3) tdec(2) drop(i.fyear) nocons addtext(Firm FE, Y, Year FE, Y)    
Output\C4.xls
dir : seeout

. 
end of do-file

. log close
      name:  <unnamed>
       log:  C:\Users\ibabenko\ASU Dropbox\Ilona Babenka\_NONPROFIT CEO PAY\RFS_code\RFS_CodeFinal\Logfile_rfs_may2025.log
  log type:  text
 closed on:  22 May 2025, 13:24:44
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